Search SciRate

In this paper, we present an unconditionally secure $N$-party comparison scheme based on Shamir secret sharing, utilizing the binary representation of private inputs to determine the $\max$ without disclosing any private inputs or intermediate results. Specifically, each party holds a private number and aims to ascertain the greatest number among the $N$ available private numbers without revealing its input, assuming that there are at most $T < \frac{N}{2}$ honest-but-curious parties. The proposed scheme demonstrates a lower computational complexity compared to existing schemes that can only compare two secret numbers at a time. To the best of our knowledge, our scheme is the only information-theoretically secure method for comparing $N$ private numbers without revealing either the private inputs or any intermediate results. We demonstrate that by modifying the proposed scheme, we can compute other well-known non-polynomial functions of the inputs, including the minimum, median, and rank. Additionally, in the proposed scheme, before the final reveal phase, each party possesses a share of the result, enabling the nodes to compute any polynomial function of the comparison result. We also explore various applications of the proposed comparison scheme, including federated learning.

In recent years, interest in vision-language tasks has grown, especially those involving chart interactions. These tasks are inherently multimodal, requiring models to process chart images, accompanying text, underlying data tables, and often user queries. Traditionally, Chart Understanding (CU) relied on heuristics and rule-based systems. However, recent advancements that have integrated transformer architectures significantly improved performance. This paper reviews prominent research in CU, focusing on State-of-The-Art (SoTA) frameworks that employ transformers within End-to-End (E2E) solutions. Relevant benchmarking datasets and evaluation techniques are analyzed. Additionally, this article identifies key challenges and outlines promising future directions for advancing CU solutions. Following the PRISMA guidelines, a comprehensive literature search is conducted across Google Scholar, focusing on publications from Jan'20 to Jun'24. After rigorous screening and quality assessment, 32 studies are selected for in-depth analysis. The CU tasks are categorized into a three-layered paradigm based on the cognitive task required. Recent advancements in the frameworks addressing various CU tasks are also reviewed. Frameworks are categorized into single-task or multi-task based on the number of tasks solvable by the E2E solution. Within multi-task frameworks, pre-trained and prompt-engineering-based techniques are explored. This review overviews leading architectures, datasets, and pre-training tasks. Despite significant progress, challenges remain in OCR dependency, handling low-resolution images, and enhancing visual reasoning. Future directions include addressing these challenges, developing robust benchmarks, and optimizing model efficiency. Additionally, integrating explainable AI techniques and exploring the balance between real and synthetic data are crucial for advancing CU research.

Internet of Things (IoT) devices are capable of allowing for far-reaching access to and evaluation of patient data to monitor health and diagnose from a distance. An electronic healthcare system that checks patient data, prepares medicines and provides financial assistance is necessary. Providing safe data transmission, monitoring, decentralization, preserving patient privacy, and maintaining confidentiality are essential to an electronic healthcare system. In this study, we introduce (SCALHEALTH) which is a blockchain-based scheme of the Hyperledger Fabric consortium. In this study, we use authentication to agree on a common key for data encryption to send data confidentially. Also, sending data through IPFS is decentralized. Non-fungible token (NFT) is used to send patient prescriptions to pharmacies and insurance companies to ensure the authenticity of patient prescriptions. As the system's main body, blockchain creates authorization and validation for all devices and institutions. Also, all metadata in the system is recorded on the blockchain to maintain integrity, transparency, and timely data monitoring. The proposed study uses two types of blockchain: a health blockchain and a financial blockchain. The financial blockchain is for financial transactions and is based on Ethereum. The health blockchain also introduces a mechanism that allows several blockchains to be active in parallel, instead of only one blockchain. The prototype of this mechanism is simulated in two scenarios. In comparison to the normal state, the proposed plan has superior results.

In recent years, the healthcare sector's shift to online platforms has spotlighted challenges concerning data security, privacy, and scalability. Blockchain technology, known for its decentralized, secure, and immutable nature, emerges as a viable solution for these pressing issues. This article presents an innovative Electronic Health Records (EHR) sharing and drug supply chain management framework tailored to address scalability, security, data integrity, traceability, and secure data sharing. The framework introduces five layers and transactions, prioritizing patient-centric healthcare by granting patients comprehensive access control over their health information. This access facilitates smoother processes, such as insurance claims, while maintaining robust security measures. Notably, our implementation of parallelism significantly bolsters scalability and transaction throughput while minimizing network traffic. Performance evaluations conducted through the Caliper benchmark indicate a slight increase in processor consumption during specific transactions, mitigated effectively by parallelization. RAM requirements remain largely stable. Additionally, our approach notably reduces network traffic while tripling transaction throughput. The framework ensures patient privacy, data integrity, access control, and interoperability, aligning with traditional healthcare systems. Moreover, it provides transparency and real-time drug supply monitoring, empowering decision-makers with actionable insights. As healthcare evolves, our framework sets a crucial precedent for innovative, scalable, and secure systems. Future enhancements could focus on scalability, real-world deployment, standardized data formats, reinforced security protocols, privacy preservation, and IoT integration to comply with regulations and meet evolving industry needs.

Random binning is a widely utilized tool in information theory, finding applications in various domains. In this paper, we focus on the output statistics of random binning (OSRB) using the Tsallis divergence $T_\alpha$. Our investigation encompasses all values of $\alpha$ within the range of $(0,\infty)$. The proofs provided in this paper cover both the achievability and converse aspects. To accommodate the unbounded nature of $T_\infty$, we analyze the OSRB framework using the Rényi's divergence criterion with the order of infinity, denoted as $D_\infty$. During our exploration of OSRB, we encounter a specific form of Rényi's conditional entropy and delve into its properties. Additionally, we demonstrate the effectiveness of this framework in establishing achievability results for wiretap channel, where Tsallis divergence serves as a security measure.

Inference centers need more data to have a more comprehensive and beneficial learning model, and for this purpose, they need to collect data from data providers. On the other hand, data providers are cautious about delivering their datasets to inference centers in terms of privacy considerations. In this paper, by modifying the structure of the autoencoder, we present a method that manages the utility-privacy trade-off well. To be more precise, the data is first compressed using the encoder, then confidential and non-confidential features are separated and uncorrelated using the classifier. The confidential feature is appropriately combined with noise, and the non-confidential feature is enhanced, and at the end, data with the original data format is produced by the decoder. The proposed architecture also allows data providers to set the level of privacy required for confidential features. The proposed method has been examined for both image and categorical databases, and the results show a significant performance improvement compared to previous methods.

The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data is commonly stored in the cloud, making it difficult for users to control and protect their information. Moreover, the recent rise in security and surveillance breaches in the healthcare industry has highlighted the need for a better approach to data storage and protection. Traditional models that rely on third-party control over patients' healthcare data are no longer reliable, as they have proven vulnerable to security breaches. To address these issues, blockchain technology has emerged as a promising solution. Blockchain-based protocols have the potential to provide a secure and efficient system for e-health applications that does not require trust in third-party intermediaries. The proposed protocol outlined in this paper uses a blockchain-based approach to manage patient data securely and efficiently. Unlike Bitcoin, which is primarily used for financial transactions, the protocol described here is designed specifically for e-health applications. It employs a consensus mechanism that is more suitable for resource constrained IoT devices, thereby reducing network costs and increasing efficiency. The proposed protocol also provides a privacy-preserving access control mechanism that enables patients to have more control over their healthcare data. By leveraging blockchain technology, the protocol ensures that only authorized individuals can access the patient's data, which helps prevent data breaches and other security issues. Finally, the security and privacy of the proposed protocol are analysed to ensure that it meets the necessary standards for data protection.

In this paper, we present a private voting system that consists of N authorized voters who may vote to one of the K candidates or vote abstain. Each voter wants to compute the final tally while staying private and robust against malicious voters, who try to gain information about the vote of the other voters beyond the final result, or send incorrect information to affect the final tally. We design an information-theoretic private voting system based on Shamir secret sharing, which is secure and robust as long as there are up to (N-1)/3 malicious voters.

The conversational agents is one of the most interested topics in computer science field in the recent decade. Which can be composite from more than one subject in this field, which you need to apply Natural Language Processing Concepts and some Artificial Intelligence Techniques such as Deep Learning methods to make decision about how should be the response. This paper is dedicated to discuss the system architecture for the conversational agent and explain each component in details.

With the advent of the Internet of Things (IoT), e-health has become one of the main topics of research. Due to the sensitivity of patient information, patient privacy seems challenging. Nowadays, patient data is usually stored in the cloud in healthcare programs, making it difficult for users to have enough control over their data. The recent increment in announced cases of security and surveillance breaches compromising patients' privacy call into question the conventional model, in which third-parties gather and control immense amounts of patients' Healthcare data. In this work, we try to resolve the issues mentioned above by using blockchain technology. We propose a blockchain-based protocol suitable for e-health applications that does not require trust in a third party and provides an efficient privacy-preserving access control mechanism. Transactions in our proposed system, unlike Bitcoin, are not entirely financial, and we do not use conventional methods for consensus operations in blockchain like Proof of Work (PoW). It is not suitable for IoT applications because IoT devices have resources-constraints. Usage of appropriate consensus method helps us to increase network security and efficiency, as well as reducing network cost, i.e., bandwidth and processor usage. Finally, we provide security and privacy analysis of our proposed protocol.

Attribute-based encryption (ABE) is a promising cryptographic mechanism for providing confidentiality and fine-grained access control in the cloud-based area. However, due to high computational overhead, common ABE schemes are not suitable for resource-constrained devices. Moreover, data owners should be able to update their defined access policies efficiently, and in some cases, applying hidden access policies is required to preserve the privacy of clients and data. In this paper, we propose a ciphertext-policy attribute-based access control scheme which for the first time provides online/offline encryption, hidden access policy, and access policy update simultaneously. In our scheme, resource-constrained devices are equipped with online/offline encryption reducing the encryption overhead significantly. Furthermore, attributes of access policies are hidden such that the attribute sets satisfying an access policy cannot be guessed by other parties. Moreover, data owners can update their defined access policies while outsourcing a major part of the updating process to the cloud service provider. In particular, we introduce blind access policies that enable the cloud service provider to update the data owners' access policies without receiving a new re-encryption key. Besides, our scheme supports fast decryption such that the decryption algorithm consists of a constant number of bilinear pairing operations. The proposed scheme is proven to be secure in the random oracle model and under the hardness of Decisional Bilinear Diffie-Hellman (DBDH) and Decision Linear (D-Linear) assumptions. Also, performance analysis results demonstrate that the proposed scheme is efficient and practical.

We have recently proposed two pile loading controllers that learn from human demonstrations: a neural network (NNet) [1] and a random forest (RF) controller [2]. In the field experiments the RF controller obtained clearly better success rates. In this work, the previous findings are drastically revised by experimenting summer time trained controllers in winter conditions. The winter experiments revealed a need for additional sensors, more training data, and a controller that can take advantage of these. Therefore, we propose a revised neural controller (NNetV2) which has a more expressive structure and uses a neural attention mechanism to focus on important parts of the sensor and control signals. Using the same data and sensors to train and test the three controllers, NNetV2 achieves better robustness against drastically changing conditions and superior success rate. To the best of our knowledge, this is the first work testing a learning-based controller for a heavy-duty machine in drastically varying outdoor conditions and delivering high success rate in winter, being trained in summer.

We study learning algorithms when there is a mismatch between the distributions of the training and test datasets of a learning algorithm. The effect of this mismatch on the generalization error and model misspecification are quantified. Moreover, we provide a connection between the generalization error and the rate-distortion theory, which allows one to utilize bounds from the rate-distortion theory to derive new bounds on the generalization error and vice versa. In particular, the rate-distortion based bound strictly improves over the earlier bound by Xu and Raginsky even when there is no mismatch. We also discuss how "auxiliary loss functions" can be utilized to obtain upper bounds on the generalization error.

We study the problem of joint information and energy transfer in a binary two-hop channel with an energy harvesting relay. We consider a finite battery size at the relay and energy loss in transmitting energy. In other words, to be able to send an energy-contained symbol, the relay must receive multiple energy-contained symbols. Thus, we face a kind of channel with memory. We model the energy saved in the battery as the channel state with the challenge that the receiver does not know the channel state. We propose two different achievable schemes, the first one is based on state-dependent superposition coding and the second one is based on the equivalent timing channel approach. Both of our schemes are based on block Markov coding and backward decoding techniques. Due to these two approaches, we find achievable rates with a single-letter expression for the model.

In this work, we consider the problem of secure multi-party computation (MPC), consisting of $\Gamma$ sources, each has access to a large private matrix, $N$ processing nodes or workers, and one data collector or master. The master is interested in the result of a polynomial function of the input matrices. Each source sends a randomized functions of its matrix, called as its share, to each worker. The workers process their shares in interaction with each other, and send some results to the master such that it can derive the final result. There are several constraints: (1) each worker can store a function of each input matrix, with the size of $\frac{1}{m}$ fraction of that input matrix, (2) up to $t$ of the workers, for some integer $t$, are adversary and may collude to gain information about the private inputs or can do malicious actions to make the final result incorrect. The objective is to design an MPC scheme with the minimum number the workers, called the recovery threshold, such that the final result is correct, workers learn no information about the input matrices, and the master learns nothing beyond the final result. In this paper, we propose an MPC scheme that achieves the recovery threshold of $3t+2m-1$ workers, which is order-wise less than the recovery threshold of the conventional methods. The challenge in dealing with this set up is that when nodes interact with each other, the malicious messages that adversarial nodes generate propagate through the system, and can mislead the honest nodes. To deal with this challenge, we design some subroutines that can detect erroneous messages, and correct or drop them.

Sharing resource blocks in NOMA systems provides more opportunity to the internal users to overhear the messages of the other users. Therefore, some sort of secrecy against the internal users in addition to the external eavesdroppers must be provided. In this paper, we investigate the secrecy performance of a two-user NOMA system in existence of the external and internal passive eavesdroppers, where the far user acts as an internal eavesdropper and tries to overhear the message of the near user. Our system consists of a single antenna base station, two legitimate users and an external passive eavesdropper. We present the closed-forms for the ergodic secrecy rates of the users. Moreover, to derive the secrecy outage probability (SOP) of the system, we use Gaussian-Chebyshev quadrature method, which gives an approximation for the SOP. Numerical results show that this approximation is very close to the exact value of the SOP of the system. Finally, we eliminate the external eavesdropper and present the closed-forms for the ergodic rate of the far user, the ergodic secrecy rate of the near user and also the SOP of the system.

Enabling cooperation in a NOMA system is a promising approach to improve its performance. In this paper, we study the cooperation in a secure NOMA system, where the legitimate users are distributed uniformly in the network and the eavesdroppers are distributed according to a homogeneous Poisson point process. We consider a cooperative NOMA scheme (two users are paired as strong and weak users) in two phases: 1) Direct transmission phase, in which the base station broadcasts a superposition of the messages, 2) Cooperation phase, in which the strong user acts as a relay to help in forwarding the messages of the weak user. We study the secrecy outage performance in two cases: (i) security of the strong user, (ii) security of both users, are guaranteed. In the first case, we derive the exact secrecy outage probability of the system for some regions of power allocation coefficients and a lower bound on the secrecy outage probability is derived for the other regions. In the second case, the strong user is a relay or a friendly jammer (as well as a relay), where an upper bound on the secrecy outage probability is derived at high signal-to-noise-ratio regimes. For both cases, the cooperation in a two-user paired NOMA system necessitate to utilize the joint distribution of the distance between two random users. Numerical results shows the superiority of the secure cooperative NOMA for a range of the cooperation power compared to secure non-cooperative NOMA systems.

Most of the security services in the connected world of cyber-physical systems necessitate authenticating a large number of nodes privately. In this paper, the private authentication problem is considered which consists of a certificate authority, a verifier (or some verifiers), many legitimate users (provers), and an arbitrary number of attackers. Each legitimate user wants to be authenticated (using his personal key) by the verifier(s), while simultaneously staying completely anonymous (even to the verifier). On the other hand, an attacker must fail to be authenticated. We analyze this problem from an information-theoretical perspective and propose a general interactive information-theoretic model for the problem. As a metric to measure the reliability, we consider the normalized total key rate whose maximization has a trade-off with establishing privacy. The problem is considered in two different scenarios: single-server scenario (only one verifier is considered, which all the provers are connected to) and multi-server scenario ($N$ verifiers are assumed, where each verifier is connected to a subset of users). For both scenarios, two regimes are considered: finite size regime (i.e., the variables are elements of a finite field) and asymptotic regime (i.e., the variables are considered to have large enough length). We propose achievable schemes that satisfy the completeness, soundness, and privacy properties in both single-server and multi-server scenarios in all cases. In the finite size regime, the main idea is to generate the authentication keys according to a secret sharing scheme. We show that the proposed scheme in the special case of multi-server authentication in the finite size regime is optimal. In the asymptotic regime, we use a random binning based scheme that relies on the joint typicality to generate the authentication keys.

In this paper, we introduce a new measure of correlation for bipartite quantum states. This measure depends on a parameter $\alpha$, and is defined in terms of vector-valued $L_p$-norms. The measure is within a constant of the exponential of $\alpha$-Rényi mutual information, and reduces to the trace norm (total variation distance) for $\alpha=1$. We will prove some decoupling type theorems in terms of this measure of correlation, and present some applications in privacy amplification as well as in bounding the random coding exponents. In particular, we establish a bound on the secrecy exponent of the wiretap channel (under the total variation metric) in terms of the $\alpha$-Rényi mutual information according to \emphCsiszár's proposal.

Polar codes are novel and efficient error correcting codes with low encoding and decoding complexities. These codes have a channel dependent generator matrix which is determined by the code dimension, code length and transmission channel parameters. This paper studies a variant of the McEliece public key cryptosystem based on polar codes, called "PKC-PC". Due to the fact that the structure of polar codes' generator matrix depends on the parameters of channel, we used an efficient approach to conceal their generator matrix. Then, by the help of the characteristics of polar codes and also introducing an efficient approach, we reduced the public and private key sizes of the PKC-PC and increased its information rate compared to the McEliece cryptosystem. It was shown that polar codes are able to yield an increased security level against conventional attacks and possible vulnerabilities on the code-based public key cryptosystems. Moreover, it is indicated that the security of the PKC-PC is reduced to solve NP-complete problems. Compared to other post-quantum public key schemes, we believe that the PKC-PC is a promising candidate for NIST post-quantum crypto standardization.

Due to hostile environment and wireless communication channel, security mechanisms are essential for wireless sensor networks (WSNs). Existence of a pair of shared key is a prerequisite for many of these security mechanisms; a task that key management system addresses. Recently, an energy efficient method based on public key cryptography (PKC) was proposed. We analyze this protocol and show that it is vulnerable to denial of service (DOS) attacks and adversary can exhaust memory and battery of nodes. Then, we analyze this protocol and show that using a more knowledgeable BS this vulnerability can be solved very efficiently. Based on this observation we propose a modified version of the protocol that achieves immediate authentication and can prevent DOS attacks. We show that the improved protocol achieves immediate authentication at the expense of 1.82 mj extra energy consumption while retaining other desirable characteristics of the basic method.

Joint encryption-encoding schemes have been released to fulfill both reliability and security desires in a single step. Using Low Density Parity Check (LDPC) codes in joint encryption-encoding schemes, as an alternative to classical linear codes, would shorten the key size as well as improving error correction capability. In this article, we present a joint encryption-encoding scheme using Quasi Cyclic-Low Density Parity Check (QC-LDPC) codes based on finite geometry. We observed that our proposed scheme not only outperforms its predecessors in key size and transmission rate, but also remains secure against all known cryptanalyses of code-based secret key cryptosystems. We subsequently show that our scheme benefits from low computational complexity. In our proposed joint encryption-encoding scheme, by taking the advantage of QC-LDPC codes based on finite geometries, the key size decreases to 1/5 of that of the so far best similar system. In addition, using our proposed scheme a wide range of desirable transmission rates are achievable. This variety of codes makes our cryptosystem suitable for a number of different communication and cryptographic standards.

This paper investigates the multiplicative spread spectrum watermarking method for the image. The information bit is spreaded into middle-frequency Discrete Cosine Transform (DCT) coefficients of each block of an image using a generated pseudo-random sequence. Unlike the conventional signal modeling, we suppose that both signal and noise are distributed with Laplacian distribution because the sample loss of digital media can be better modeled with this distribution than the Gaussian one. We derive the optimum decoder for the proposed embedding method thanks to the maximum likelihood decoding scheme. We also analyze our watermarking system in the presence of noise and provide analytical evaluations and several simulations. The results show that it has the suitable performance and transparency required for watermarking applications.

We study the problem of joint information and energy transfer in a two-hop channel with a Radio frequency (RF) energy harvesting relay. We consider a finite battery size at the relay and deterministic energy loss in transmitting energy. In other words, to be able to send an energy-contained symbol, the relay must receive multiple energy-contained symbols. Thus, we face a kind of channel with memory. We model the energy saved in battery as channel state with the challenge that the receiver does not know the channel state. First, we consider the problem without any channel noise and derive an achievable rate. Next, we extend the results to the case with an independent and identically distributed noise in the second hop (the relay-receiver link).

Security is a critical and vital task in wireless sensor networks, therefore different key management systems have been proposed, many of which are based on symmetric cryptography. Such systems are very energy efficient, but they lack some other desirable characteristics. On the other hand, systems based on public key cryptography have those desirable characteristics, but they consume more energy. Recently based on authenticated messages from base station a new PKC based key agreement protocol was proposed. We show this method is susceptible to a form of denial of service attack where resources of the network can be exhausted with bogus messages. Then, we propose two different improvements to solve this vulnerability. Simulation results show that these new protocols retain desirable characteristics of the basic method and solve its deficiencies.

Energy harvesting (EH) has been developed to extend the lifetimes of energy-limited communication systems. In this letter, we consider a single-user EH communication system, in which both of the arrival data and the harvested energy curves are modeled as general functions. Unlike most of the works in the field, we investigate the online algorithms which only acquire the causal information of the arrival data and the harvested energy processes. We study how well the optimal online algorithm works compared with the optimal offline algorithm, and thus our goal is to find the lower and upper bounds for the ratio of the completion time in the optimal online algorithm to the optimal offline algorithm. We propose two online algorithms which achieve the upper bound of 2 on this ratio. Also, we show that this ratio is 2 for the optimal online algorithm.

In this paper, we consider a multi-hop energy harvesting (EH) communication system in a full-duplex mode, where arrival data and harvested energy curves in the source and the relays are modeled as general functions. This model includes the EH system with discrete arrival processes as a special case. We investigate the throughput maximization problem considering minimum utilized energy in the source and relays and find the optimal offline algorithm. We show that the optimal solution of the two-hop transmission problem have three main steps: (i) Solving a point-to-point throughput maximization problem at the source; (ii) Solving a point-to-point throughput maximization problem at the relay (after applying the solution of first step as the input of this second problem); (iii) Minimizing utilized energy in the source. In addition, we show that how the optimal algorithm for the completion time minimization problem can be derived from the proposed algorithm for throughput maximization problem. Also, for the throughput maximization problem, we propose an online algorithm and show that it is more efficient than the benchmark one (which is a direct application of an existing point-to-point online algorithm to the multi-hop system).

In this paper, we show the equivalency of weak and strong secrecy conditions for a large class of secure network coding problems. When we restrict to linear operations, we show the equivalency of "perfect secrecy and zero-error constraints" with "weak secrecy and $\epsilon$-error constraints".

In this paper we consider the State-Dependent Wiretap Channel (SD-WC). As the main idea, we model the SD-WC as a Cognitive Interference Channel (CIC), in which the primary receiver acts as an eavesdropper for the cognitive transmitter's message. By this point of view, the Channel State Information (CSI) in SD-WC plays the role of the primary user's message in CIC which can be decoded at the eavesdropper. This idea enables us to use the main achievability approaches of CIC, i.~e., Gel'fand-Pinsker Coding (GPC) and Superposition Coding (SPC), to find new achievable equivocation-rates for the SD-WC. We show that these approaches meet the capacity under some constraints on the rate of the channel state. Similar to the dirty paper channel, extending the results to the Gaussian case shows that the GPC lead to the capacity of the Gaussian SD-WC which is equal to the capacity of the wiretap channel without channel state. Hence, we achieve the capacity of the Gaussian SD-WC using the dirty paper technique. Moreover, our proposed approaches provide the capacity of the Binary SD-WC. It is shown that the capacity of the Binary SD-WC is equal to the capacity of the Binary wiretap channel without channel state.

In this paper, we consider the problem of the interference alignment for the $K$-user SISO interference channel (IC) with blind channel state information (CSI) at transmitters. Our achievement in contrast to the traditional $K-$user interference alignment (IA) scheme has more practical notions. In this case, every receiver is equipped with one reconfigurable antenna which tries to place its desired signal in a subspace which is linearly independent of interference signals. We show that if the channel values are known to the receivers only, the sum degrees-of-freedom (DoF) of the linear blind IA (BIA) with reconfigurable antenna is $\frac{Kr}{r^2-r+K}$, where $r = \left \lceil{\frac{\sqrt{1+4K}-1}{2}} \right \rceil$. The result indicates that the optimum sum DoF for the $K-$user IC is to achieve the sum DoF of $\lim_{K \rightarrow \infty} {\frac{Kr}{r^2-r+K}}=\frac{\sqrt{K}}{2}$ for an asymptotically large interference network. Thus, the DoF of the $K$-user IC using reconfigurable antenna grows sublinearly with the number of the users, whereas it grows linearly in the case where transmitters access to the CSI. In addition, we propose both achievability and converse proof so as to show that this is the sum DoF of linear BIA with the reconfigurable antenna.

In this paper, an extended large wireless network under the secrecy constraint is considered. In contrast to works which use idealized assumptions, a more realistic network situation with unknown eavesdroppers locations is investigated: the legitimate users only know their own Channel State Information (CSI), not the eavesdroppers CSI. Also, the network is analyzed by taking in to account the effects of both fading and path loss. Under these assumptions, a power efficient cooperative scheme, named \emphstochastic virtual beamforming, is proposed. Applying this scheme, an unbounded secure rate with any desired outage level is achieved, provided that the density of the legitimate users tends to infinity. In addition, by tending the legitimate users density to the infinity, the tolerable density of eavesdroppers will become unbounded too.

In this paper, we consider the problem of the interference alignment for the $K$-user SISO interference channel with blind channel state information at transmitters (CSIT). Our achievement in contrast to popular $K-$user interference alignment (IA) scheme has more practical notions. In this case every receiver is equipped with one reconfigurable antenna which tries to place its desired signal in a subspace which is linearly independent from interference signals. We show that if the channel values are known to the receivers only, the sum degrees-of-freedom (DOF) rate region of the linear BIA with staggered antenna switching is $\frac{Kr}{r^2-r+K}$, where $r = \left \lceil{\frac{\sqrt{1+4K}-1}{2}} \right \rceil$. The result indicates that the optimum DoF rate region of the $K-$user interference channel is to achieve the DoF of $\frac{\sqrt{K}}{2}$ for an asymptotically large network. Thus, the DoF of the $K$-user interference channel using staggered antenna switching grows sub-linearly with the number of the users, whereas it grows linearly in the case where transmitters access the CSI. In addition we propose both achievability and converse proof so as to show that this is the DoF rate region of blind interference alignment (BIA) with staggered antenna switching.

In this paper we explore the information-theoretic aspects of interference alignment and its relation to channel state information (CSI). For the $K-$user interference channel using different changing patterns between different users, we propose several methods to align some parts of interferences and to increase what is achieved by time sharing method. For more practical case when all the channel links connected to the same destination have the same changing pattern, we find an upper-bound and analyze it for the large interference channel network. This result shows that when the size of the network increases, the upper-bound value goes to $\frac{\sqrt{K}}{2}$. For the fast fading channel when all the channels have the same changing pattern, we show that when the direct links have different characteristic functions (channel permutation or memory), in the absence of half part of CSI (cross links) at both transmitters and receivers, one can achieve $K/2$ degrees-of-freedom (DoF). Also by the converse proof we show that this is the minimum channel information to achieve maximum DoF of $\frac{K}{2}$. Throughout this work, this fact has been pinpointed to prove statements about more general partial state CSI and achievable DoF. In other words, for the 3-user fully connected interference channel we find out while $\frac{3}{2}$ lies in achievable DoF, we don't need to know half part of the CSI. Also, the result has been extended to a more general form for $K-$user interference channel and through the converse proof, its functionality on channel state is proved to be optimum.

The secrecy problem in the state-dependent cognitive interference channel is considered in this paper. In our model, there are a primary and a secondary (cognitive) transmitter-receiver pairs, in which the cognitive transmitter has the message of the primary one as side information. In addition, the channel is affected by a channel state sequence which is estimated partially at the cognitive transmitter and the corresponding receiver. The cognitive transmitter wishes to cooperate with the primary one, and it sends its individual message which should be confidential at the primary receiver. The achievable equivocation-rate regions for this channel are derived using two approaches: the binning scheme coding, and superposition coding. Then the outer bounds on the capacity are proposed and the results are extended to the Gaussian examples.

Energy harvesting has been developed as an effective technology for communication systems in order to extend the lifetime of these systems. In this work, we consider a singleuser energy harvesting wireless communication system, in which arrival data and harvested energy curves are modeled as continuous functions. For the single-user model, our first goal is to find an offline algorithm, which maximizes the amount of data which is transmitted to the receiver node by a given deadline. If more than one scheme exists that transmits the maximum data, we choose the one with minimum utilized energy at the transmitter node. Next, we propose an online algorithm for this system. We also consider a multi-hop energy harvesting wireless communication system in a full-duplex mode and find the optimal offline algorithm to maximize the throughput.

In this paper, we investigate the index coding problem in the presence of an eavesdropper. Messages are to be sent from one transmitter to a number of legitimate receivers who have side information about the messages, and share a set of secret keys with the transmitter. We assume perfect secrecy, meaning that the eavesdropper should not be able to retrieve any information about the message set. We study the minimum key lengths for zero-error and perfectly secure index coding problem. On one hand, this problem is a generalization of the index coding problem (and thus a difficult one). On the other hand, it is a generalization of the Shannon's cipher system. We show that a generalization of Shannon's one-time pad strategy is optimal up to a multiplicative constant, meaning that it obtains the entire boundary of the cone formed by looking at the secure rate region from the origin. Finally, we consider relaxation of the perfect secrecy and zero-error constraints to weak secrecy and asymptotically vanishing probability of error, and provide a secure version of the result, obtained by Langberg and Effros, on the equivalence of zero-error and $\epsilon$-error regions in the conventional index coding problem.

Join optimization has been dominated by Selinger-style, pairwise optimizers for decades. But, Selinger-style algorithms are asymptotically suboptimal for applications in graphic analytics. This suboptimality is one of the reasons that many have advocated supplementing relational engines with specialized graph processing engines. Recently, new join algorithms have been discovered that achieve optimal worst-case run times for any join or even so-called beyond worst-case (or instance optimal) run time guarantees for specialized classes of joins. These new algorithms match or improve on those used in specialized graph-processing systems. This paper asks can these new join algorithms allow relational engines to close the performance gap with graph engines? We examine this question for graph-pattern queries or join queries. We find that classical relational databases like Postgres and MonetDB or newer graph databases/stores like Virtuoso and Neo4j may be orders of magnitude slower than these new approaches compared to a fully featured RDBMS, LogicBlox, using these new ideas. Our results demonstrate that an RDBMS with such new algorithms can perform as well as specialized engines like GraphLab -- while retaining a high-level interface. We hope this adds to the ongoing debate of the role of graph accelerators, new graph systems, and relational systems in modern workloads.

We study a two-user state-dependent generalized multiple-access channel (GMAC) with correlated states. It is assumed that each encoder has \emphnoncausal access to channel state information (CSI). We develop an achievable rate region by employing rate-splitting, block Markov encoding, Gelfand--Pinsker multicoding, superposition coding and joint typicality decoding. In the proposed scheme, the encoders use a partial decoding strategy to collaborate in the next block, and the receiver uses a backward decoding strategy with joint unique decoding at each stage. Our achievable rate region includes several previously known regions proposed in the literature for different scenarios of multiple-access and relay channels. Then, we consider two Gaussian GMACs with additive interference. In the first model, we assume that the interference is known noncausally at both of the encoders and construct a multi-layer Costa precoding scheme that removes \emphcompletely the effect of the interference. In the second model, we consider a doubly dirty Gaussian GMAC in which each of interferences is known noncausally only at one encoder. We derive an inner bound and analyze the achievable rate region for the latter model and interestingly prove that if one of the encoders knows the full CSI, there exists an achievable rate region which is \emphindependent of the power of interference.

In this paper, we study the problem of secret communication over a Compound Multiple Access Channel (MAC). In this channel, we assume that one of the transmitted messages is confidential that is only decoded by its corresponding receiver and kept secret from the other receiver. For this proposed setting (compound MAC with confidential messages), we derive general inner and outer bounds on the secrecy capacity region. Also, as examples, we investigate 'Less noisy' and 'Gaussian' versions of this channel, and extend the results of the discrete memoryless version to these cases. Moreover, providing numerical examples for the Gaussian case, we illustrate the comparison between achievable rate regions of compound MAC and compound MAC with confidential messages.

In this paper, we study the problem of secret communication over a multiple-access channel with a common message. Here, we assume that two transmitters have confidential messages, which must be kept secret from the wiretapper (the second receiver), and both of them have access to a common message which can be decoded by the two receivers. We call this setting as Multiple-Access Wiretap Channel with Common message (MAWC-CM). For this setting, we derive general inner and outer bounds on the secrecy capacity region for the discrete memoryless case and show that these bounds meet each other for a special case called the switch channel. As well, for a Gaussian version of MAWC-CM, we derive inner and outer bounds on the secrecy capacity region. Providing numerical results for the Gaussian case, we illustrate the comparison between the derived achievable rate region and the outer bound for the considered model and the capacity region of compound multiple access channel.

This paper proposes an efficient secret key cryptosystem based on polar codes over Binary Erasure Channel. We introduce a method, for the first time to our knowledge, to hide the generator matrix of the polar codes from an attacker. In fact, our main goal is to achieve secure and reliable communication using finite-length polar codes. The proposed cryptosystem has a significant security advantage against chosen plaintext attacks in comparison with the Rao-Nam cryptosystem. Also, the key length is decreased after applying a new compression algorithm. Moreover, this scheme benefits from high code rate and proper error performance for reliable communication.

In this paper, we study the problem of simulating a DMC channel from another DMC channel under an average-case and an exact model. We present several achievability and infeasibility results, with tight characterizations in special cases. In particular for the exact model, we fully characterize when a BSC channel can be simulated from a BEC channel when there is no shared randomness. We also provide infeasibility and achievability results for simulation of a binary channel from another binary channel in the case of no shared randomness. To do this, we use properties of Rényi capacity of a given order. We also introduce a notion of "channel diameter" which is shown to be additive and satisfy a data processing inequality.

In this paper, we investigate the problem of the empirical coordination in a triangular multiterminal network. A triangular multiterminal network consists of three terminals where two terminals observe two external i.i.d correlated sequences. The third terminal wishes to generate a sequence with desired empirical joint distribution. For this problem, we derive inner and outer bounds on the empirical coordination capacity region. It is shown that the capacity region of the degraded source network and the inner and outer bounds on the capacity region of the cascade multiterminal network can be directly obtained from our inner and outer bounds. For a cipher system, we establish key distribution over a network with a reliable terminal, using the results of the empirical coordination. As another example, the problem of rate distortion in the triangular multiterminal network is investigated in which a distributed doubly symmetric binary source is available.

In this paper we develop a finite blocklength version of the Output Statistics of Random Binning (OSRB) framework. The framework is shown to be optimal in the point-to-point case. New second order regions for broadcast channel and wiretap channel with strong secrecy criterion are derived.

This paper proposes a novel technique to prove a one-shot version of achievability results in network information theory. The technique is not based on covering and packing lemmas. In this technique, we use an stochastic encoder and decoder with a particular structure for coding that resembles both the ML and the joint-typicality coders. Although stochastic encoders and decoders do not usually enhance the capacity region, their use simplifies the analysis. The Jensen inequality lies at the heart of error analysis, which enables us to deal with the expectation of many terms coming from stochastic encoders and decoders at once. The technique is illustrated via several examples: point-to-point channel coding, Gelfand-Pinsker, Broadcast channel (Marton), Berger-Tung, Heegard-Berger/Kaspi, Multiple description coding and Joint source-channel coding over a MAC. Most of our one-shot results are new. The asymptotic forms of these expressions is the same as that of classical results. Our one-shot bounds in conjunction with multi-dimensional Berry-Essen CLT imply new results in the finite blocklength regime. In particular applying the one-shot result for the memoryless broadcast channel in the asymptotic case, we get the entire region of Marton's inner bound without any need for time-sharing.

In this paper, the problem of secret key agreement in state-dependent multiple access channels with an eavesdropper is studied. For this model, the channel state information is non-causally available at the transmitters; furthermore, a legitimate receiver observes a degraded version of the channel state information. The transmitters can partially cooperate with each other using a conferencing link with a limited rate. In addition, a backward public channel is assumed between the terminals. The problem of secret key sharing consists of two rounds. In the first round, the transmitters wish to share a common key with the legitimate receiver. Lower and upper bounds on the common key capacity are established. In a special case, the capacity of the common key is obtained. In the second round, the legitimate receiver agrees on two independent private keys with the corresponding transmitters using the public channel. Inner and outer bounds on the private key capacity region are characterized. In a special case, the inner bound coincides with the outer bound. We provide some examples to illustrate our results.

In this paper, we consider the problem of secret key agreement in state-dependent 3-receiver broadcast channels. In the proposed model, there are two legitimate receivers, an eavesdropper and a transmitter where the channel state information is non-causally available at the transmitter. We consider two setups. In the first setup, the transmitter tries to agree on a common key with the legitimate receivers while keeping it concealed from the eavesdropper. Simultaneously, the transmitter agrees on a private key with each of the legitimate receivers that needs to be kept secret from the other legitimate receiver and the eavesdropper. For this setup, we derive inner and outer bounds on the secret key capacity region. In the second setup, we assume that a backward public channel is available among the receivers and the transmitter. Each legitimate receiver wishes to share a private key with the transmitter. For this setup, an inner bound on the private key capacity region is found. Furthermore, the capacity region of the secret key in the state-dependent wiretap channel can be deduced from our inner and outer bounds.

In this paper the Output Statistics of Random Binning (OSRB) framework is used to prove a new inner bound for the problem of secure channel simulation. Our results subsume some recent results on the secure function computation. We also provide an achievability result for the problem of simultaneously simulating a channel and creating a shared secret key. A special case of this result generalizes the lower bound of Gohari and Anantharam on the source model to include constraints on the rates of the public discussion.

This study investigates the capacity region of a three-user cognitive radio network with two primary users and one cognitive user. A three-user Cognitive Interference Channel (C-IFC) is proposed by considering a three-user Interference Channel (IFC) where one of the transmitters has cognitive capabilities and knows the messages of the other two transmitters in a non-causal manner. First, two inner bounds on the capacity region of the three-user C-IFC are obtained based on using the schemes which allow all receivers to decode all messages with two different orders. Next, two sets of conditions are derived, under which the capacity region of the proposed model coincides with the capacity region of a three-user C-IFC in which all three messages are required at all receivers. Under these conditions, referred to as strong interference conditions, the capacity regions for the proposed three-user C-IFC are characterized. Moreover, the Gaussian three-user C-IFC is considered and the capacity results are derived for the Gaussian case. Some numerical examples are also provided.

A new applicable wiretap channel with separated side information is considered here which consist of a sender, a legitimate receiver and a wiretapper. In the considered scenario, the links from the transmitter to the legitimate receiver and the eavesdropper experience different conditions or channel states. So, the legitimate receiver and the wiretapper listen to the transmitted signal through the channels with different channel states which may have some correlation to each other. It is assumed that the transmitter knows the state of the main channel non-causally and uses this knowledge to encode its message. The state of the wiretap channel is not known anywhere. An achievable equivocation rate region is derived for this model and is compared to the existing works. In some special cases, the results are extended to the Gaussian wiretap channel.

In this paper, we study the problem of channel simulation via interactive communication, known as the coordination capacity, in a two-terminal network. We assume that two terminals observe i.i.d.\ copies of two random variables and would like to generate i.i.d.\ copies of two other random variables jointly distributed with the observed random variables. The terminals are provided with two-way communication links, and shared common randomness, all at limited rates. Two special cases of this problem are the interactive function computation studied by Ma and Ishwar, and the tradeoff curve between one-way communication and shared randomness studied by Cuff. The latter work had inspired Gohari and Anantharam to study the general problem of channel simulation via interactive communication stated above. However only inner and outer bounds for the special case of no shared randomness were obtained in their work. In this paper we settle this problem by providing an exact computable characterization of the multi-round problem. To show this we employ the technique of "output statistics of random binning" that has been recently developed by the authors.

This paper introduces a new and ubiquitous framework for establishing achievability results in \emphnetwork information theory (NIT) problems. The framework uses random binning arguments and is based on a duality between channel and source coding problems. Further, the framework uses pmf approximation arguments instead of counting and typicality. This allows for proving coordination and \emphstrong secrecy problems where certain statistical conditions on the distribution of random variables need to be satisfied. These statistical conditions include independence between messages and eavesdropper's observations in secrecy problems and closeness to a certain distribution (usually, i.i.d. distribution) in coordination problems. One important feature of the framework is to enable one to add an eavesdropper and obtain a result on the secrecy rates "for free." We make a case for generality of the framework by studying examples in the variety of settings containing channel coding, lossy source coding, joint source-channel coding, coordination, strong secrecy, feedback and relaying. In particular, by investigating the framework for the lossy source coding problem over broadcast channel, it is shown that the new framework provides a simple alternative scheme to \emphhybrid coding scheme. Also, new results on secrecy rate region (under strong secrecy criterion) of wiretap broadcast channel and wiretap relay channel are derived. In a set of accompanied papers, we have shown the usefulness of the framework to establish achievability results for coordination problems including interactive channel simulation, coordination via relay and channel simulation via another channel.

In this paper, we study the problem of coordinating two nodes which can only exchange information via a relay at limited rates. The nodes are allowed to do a two-round interactive two-way communication with the relay, after which they should be able to generate i.i.d. copies of two random variables with a given joint distribution within a vanishing total variation distance. We prove inner and outer bounds on the coordination capacity region for this problem. Our inner bound is proved using the technique of "output statistics of random binning" that has recently been developed by Yassaee, et al.

A secret key agreement framework between three users is considered in which each of the users 1 and 2 intends to share a secret key with user 3 and users 1 and 2 are eavesdroppers with respect to each other. There is a generalized discrete memoryless multiple access channel (GDMMAC) from users 1 and 2 to user 3 where the three users receive outputs from the channel. Furthermore, there is a broadcast channel (BC) from user 3 to users 1 and 2. Secret key sharing is intended where GDMMAC and BC can be successively used. In this framework, an inner bound of the secret key capacity region is derived. Moreover, for a special case where the channel inputs and outputs of the GDMAC and the BC form Markov chains in some order, the secret key capacity region is derived. Also the results are discussed through a binary example.

In this paper, for a fading decode-and-forward full-duplex relay channel, we analytically derive optimum power allocations. Individual power constraints for the source and the relay are assumed and the related optimization problem is analyzed for two scenarios. First, optimization is taken over the source power, the relay power, and the correlation coefficient between the transmitted signals of the source and the relay. Then, for a fixed value of correlation coefficient, the optimization problem is analyzed. It is also proven that the optimization problems are convex for these two scenarios. Finally, implications of theoretical results are discussed through simulations for each scenario.

In this paper, taking into account the effect of link delays, we investigate the capacity region of the Cognitive Interference Channel (C-IFC), where cognition can be obtained from either causal or non-causal generalized feedback. For this purpose, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user's transmission can depend on $L$ future received symbols as well as the past ones. We show that the CC-IFC-WD model is equivalent to a classical Causal C-IFC (CC-IFC) with link delays. Moreover, CC-IFC-WD extends both genie-aided and causal cognitive radio channels and bridges the gap between them. First, we derive an outer bound on the capacity region for the arbitrary value of $L$ and specialize this general outer bound to the strong interference case. Then, under strong interference conditions, we tighten the outer bound. To derive the achievable rate regions, we concentrate on three special cases: 1) Classical CC-IFC (L=0), 2) CC-IFC without delay (L=1), and 3) CC-IFC with unlimited look-ahead in which the cognitive user non-causally knows its entire received sequence. In each case, we obtain a new inner bound on the capacity region. Moreover, we show that the coding strategy which we use to derive an achievable rate region for the classical CC-IFC achieves the capacity for the classes of degraded and semi-deterministic classical CC-IFC under strong interference conditions. Furthermore, we extend our achievable rate regions to the Gaussian case. Providing some numerical examples for Gaussian CC-IFC-WD, we compare the performances of the different strategies and investigate the rate gain of the cognitive link for different delay values.

We consider a relay network with two relays and two feedback links from the relays to the sender. To obtain the achievability results, we use the compress-and-forward and the decode-and-forward strategies to superimpose facility and cooperation analogue to what proposed by Cover and El Gamal for a relay channel. In addition to random binning, we use deterministic binning to perform restricted decoding. We show how to use the feedback links for cooperation between the sender and the relays to transmit the information which is compressed in the sender and the relays.

We consider a relay network with two relays and a feedback link from the receiver to the sender. To obtain the achievability result, we use compress-and-forward and random binning techniques combined with deterministic binning and restricted decoding. Moreover, we use joint decoding technique to decode the relays' compressed information to achieve a higher rate in the receiver.

A new scenario for generating a secret key and two private keys among three Terminals in the presence of an external eavesdropper is considered. Terminals 1, 2 and 3 intend to share a common secret key concealed from the external eavesdropper (Terminal 4) and simultaneously, each of Terminals 1 and 2 intends to share a private key with Terminal 3 while keeping it concealed from each other and from Terminal 4. All four Terminals observe i.i.d. outputs of correlated sources and there is a public channel from Terminal 3 to Terminals 1 and 2. An inner bound of the "secret key-private keys capacity region" is derived and the single letter capacity regions are obtained for some special cases.

This paper investigates the capacity problem for some multiple-access scenarios with cooperative transmitters. First, a general Multiple-Access Channel (MAC) with common information, i.e., a scenario where p transmitters send private messages and also a common message to q receivers and each receiver decodes all of the messages, is considered. The capacity region of the discrete memoryless channel is characterized. Then, the general Gaussian fading MAC with common information wherein partial Channel State Information (CSI) is available at the transmitters (CSIT) and perfect CSI is available at the receivers (CSIR) is investigated. A coding theorem is proved for this model that yields an exact characterization of the throughput capacity region. Finally, a two-transmitter/one-receiver Gaussian fading MAC with conferencing encoders with partial CSIT and perfect CSIR is studied and its capacity region is determined. For the Gaussian fading models with CSIR only (transmitters have no access to CSIT), some numerical examples and simulation results are provided for Rayleigh fading.

In this paper, we present a new method for variable elimination in systems of inequations which is much faster than the Fourier-Motzkin Elimination (FME) method. In our method, a linear Diophantine problem is introduced which is dual to our original problem. The new Diophantine system is then solved, and the final result is calculated by finding the dual inequations system. Our new method uses the algorithm Normaliz to find the Hilbert basis of the solution space of the given Diophantine problem. We introduce a problem in the interference channel with multiple nodes and solve it with our new method. Next, we generalize our method to all problems involving FME and in the end we compare our method with the previous method. We show that our method has many advantages in comparison to the previous method. It does not produce many of the redundant answers of the FME method. It also solves the whole problem in one step whereas the previous method uses a step by step approach in eliminating each auxiliary variable.

In this paper, a two-user discrete memoryless multiple-access channel (DM-MAC) with correlated channel states, each known at one of the encoders is considered, in which each encoder transmits independent messages and tries to cooperate with the other one. To consider cooperating encoders, it is assumed that each encoder strictly-causally receives and learns the other encoder's transmitted symbols and tries to cooperate with the other encoder by transmitting its message. Next, we study this channel in a special case; we assume that the common part of both states is known at both, hence encoders use this opportunity to get better rate region. For these scenarios, an achievable rate region is derived based on a combination of block-Markov encoding and Gel'fand-Pinsker coding techniques. Furthermore, the achievable rate region is established for the Gaussian channel, and it is shown that the capacity region is achieved in certain circumstances.

In this paper, we introduce a discrete memoryless State-Dependent Relay Channel with Private Messages (SD-RCPM) as a generalization of the state-dependent relay channel. We investigate two main cases: SD-RCPM with non-causal Channel State Information (CSI), and SD-RCPM with causal CSI. In each case, it is assumed that partial CSI is available at the source and relay. For non-causal case, we establish an achievable rate region using Gel'fand-Pinsker type coding scheme at the nodes informed of CSI, and Compress-and-Forward (CF) scheme at the relay. Using Shannon's strategy and CF scheme, an achievable rate region for causal case is obtained. As an example, the Gaussian version of SD-RCPM is considered, and an achievable rate region for Gaussian SD-RCPM with non-causal perfect CSI only at the source, is derived. Providing numerical examples, we illustrate the comparison between achievable rate regions derived using CF and Decode-and-Forward (DF) schemes.

We consider the Gaussian Dirty Tape Channel (DTC) Y=X+S+Z, where S is an additive Gaussian interference known causally to the transmitter. The general expression [max]\_top(P_U,f(.),X=f(U,S))I(U;Y) is presented for the capacity of this channel. For linear assignment to f(.), i.e. X=U-\betaS, this expression leads to the compensation strategy proposed previously by Willems to obtain an achievable rate for the DTC. We show that linear assignment to f(.) is optimal, under the condition that there exists a real number \beta^* such that the pair (X+\beta^* S,U) is independent of interference S. Furthermore, by applying a time-sharing technique to the achievable rate derived by linear assignment to f(.), an improved lower bound on the capacity of DTC is obtained. We also consider the Gaussian multiple access channel with additive interference, and study two different scenarios for this system. In the first case, both transmitters know interference causally while in the second, one transmitter has access to the interference noncausally and the other causally. Achievable rate regions for these two scenarios are then established.

In this paper, new inner and outer bounds on the achievable compression-equivocation rate region for generalized secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and Charlie intend to transmit information to Bob via channels with limited capacity so that he can reliably reconstruct their observations. The eavesdropper, Eve, has access to one of the channels at each instant and is interested in the source of the same channel at the time. Bob and Eve also have their own observations which are correlated with Alice's and Charlie's observations. In this model, two equivocation and compression rates are defined with respect to the sources of Alice and Charlie. Furthermore, different special cases are discussed where the inner and outer bounds match. Our model covers the previously obtained results as well.

A source model for secret key generation between terminals is considered. Two users, namely users 1 and 2, at one side communicate with another user, namely user 3, at the other side via a public channel where three users can observe i.i.d. outputs of correlated sources. Each of users 1 and 2 intends to share a secret key with user 3 where user 1 acts as a wiretapper for user 2 and vice versa. In this model, two situations are considered: communication from users 1 and 2 to user 3 (the forward key strategy) and from user 3 to users 1 and 2 (the backward key strategy). In both situations, the goal is sharing a secret key between user 1 and user 3 while leaking no effective information about that key to user 2, and simultaneously, sharing another secret key between user 2 and user 3 while leaking no effective information about the latter key to user 1. This model is motivated by wireless communications when considering user 3 as a base station and users 1 and 2 as network users. In this paper, for both the forward and backward key strategies, inner and outer bounds of secret key capacity regions are derived. In special situations where one of users 1 and 2 is only interested in wiretapping and not key sharing, our results agree with that of Ahlswede and Csiszar. Also, we investigate some special cases in which the inner bound coincides with the outer bound and secret key capacity region is deduced.

In this paper, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user transmission can depend on $L$ future received symbols as well as the past ones. Taking the effect of the link delays into account, CC-IFC-WD fills the gap between the genie-aided and causal 1cognitive radio channels. We study three special cases: 1) Classical CC-IFC (L=0), 2) CC-IFC without delay (L=1) and 3) CC-IFC with a block length delay (L=n). In each case, we obtain an inner bound on the capacity region. Our coding schemes make use of cooperative strategy by generalized block Markov superposition coding, collaborative strategy by rate splitting, and Gel'fand-Pinsker coding in order to pre-cancel part of the interference. Moreover, instantaneous relaying and non-causal partial Decode-and-Forward strategies are employed in the second and third cases, respectively. The derived regions under special conditions, reduce to several previously known results. Moreover, we show that the coding strategy which we use to derive achievable rate region for the classical CC-IFC achieves capacity for a special case of this channel. Furthermore, we extend our achievable rate regions to Gaussian case. Providing a numerical example for Gaussian CC-IFC-WD, we investigate the rate gain of the cognitive link for different delay values.

In this paper, we investigate optimal coding strategies for a class of linear deterministic relay networks. The network under study is a relay network, with one source, one destination, and two relay nodes. Additionally, there is a disturbing source of signals that causes interference with the information signals received by the relay nodes. Our model captures the effect of the interference of message signals and disturbing signals on a single relay network, or the interference of signals from multiple relay networks with each other in the linear deterministic framework. For several ranges of the network parameters we find upper bounds on the maximum achievable source--destination rate in the presense of the disturbing node and in each case we find an optimal coding scheme that achieves the upper bound.

This paper deals with the problem of multicasting a set of discrete memoryless correlated sources (DMCS) over a cooperative relay network. Necessary conditions with cut-set interpretation are presented. A \emphJoint source-Wyner-Ziv encoding/sliding window decoding scheme is proposed, in which decoding at each receiver is done with respect to an ordered partition of other nodes. For each ordered partition a set of feasibility constraints is derived. Then, utilizing the sub-modular property of the entropy function and a novel geometrical approach, the results of different ordered partitions are consolidated, which lead to sufficient conditions for our problem. The proposed scheme achieves operational separation between source coding and channel coding. It is shown that sufficient conditions are indeed necessary conditions in two special cooperative networks, namely, Aref network and finite-field deterministic network. Also, in Gaussian cooperative networks, it is shown that reliable transmission of all DMCS whose Slepian-Wolf region intersects the cut-set bound region within a constant number of bits, is feasible. In particular, all results of the paper are specialized to obtain an achievable rate region for cooperative relay networks which includes relay networks and two-way relay networks.