Random binning is a widely used technique in information theory with diverse applications. In this paper, we focus on the output statistics of random binning (OSRB) using the Tsallis divergenceTα. We analyze all values of α ∈ (0,∞)∪{∞} and consider three scenarios: (i) the binned sequence is generated i.i.d., (ii) the sequence is randomly chosen from an ϵ-typical set, and (iii) the sequence originates from an ϵ-typical set and is passed through a non-memoryless virtual channel. Our proofs cover both achievability and converse results. To address the unbounded nature ofT∞, we extend the OSRB framework via Rényi’s divergence with order infinity, denotedD∞. As part of our exploration, we analyze a specific form of Rényi’s conditional entropy and its properties. Additionally, we demonstrate the application of this framework in deriving achievability results for the wiretap channel, where Tsallis divergence serves as a security measure. The secure rate we obtain through the OSRB analysis matches the secure capacity for α ∈ (0, 2] ∪ {∞} and serves as a potential candidate for the secure capacity when α ∈ (2,∞).

Non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) systems are highly efficient. Massive MIMO systems are inherently resistant to passive attackers (eavesdroppers), thanks to transmissions directed to the users. However, active attackers can transmit a combination of legitimate user pilot signals during the channel estimation phase. This way, they can mislead the base station (BS) to rotate the transmission in their direction and allow them to eavesdrop during the downlink data transmission phase. In this paper, we analyze this vulnerability with two-user pairing strategies and investigate how physical layer security can mitigate such attacks and ensure secure (confidential) communication. We derive the secrecy outage probability (SOP) and a lower bound on the ergodic secrecy capacity using stochastic geometry tools when the number of antennas in the BSs tends to infinity (i.e., massive MIMO BS). The numerical and simulation results show that one of the strategies performs better and has a higher ergodic secrecy rate (ESR) and lower SOP. Moreover, we show that using NOMA instead of orthogonal multiple access (OMA) improves system performance significantly.

This paper proposes a multi-stage position and velocity estimation algorithm in the context of near-field (NF) integrated sensing and communications (ISAC). We consider a colocated multiple-input multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) system. Both the wavefront curvature in NF and the wideband feature of OFDM are utilized to jointly estimate the range and the angle of the targets. The proposed algorithm relies on spectral estimation methods and maximum likelihood (ML) refinement steps for target sensing. Also, the estimation performance is compared with the CramérRao lower bound (CRLB). Given the initial estimations of the targets' position and mobility parameters through our proposed algorithm, we further develop a precoding (i.e., beamfocusing) design. The proposed design exploits the finite beam depth and width in NF with minimal beam cross-correlation of different targets across both range and angular domains, allowing better overall resolution. The precoding design also accounts for a tradeoff behavior between communication and sensing performance.

In this paper, we address a physical layer security (PLS) framework for the integrated sensing and semantic communication (ISASC) system, where a multi-antenna dual-function semantic base station serves multiple single-antenna semantic communication users (SCUs) and monitors a malicious sensing target (MST), in the presence of a single-antenna eavesdropper (EVE), with both the MST and EVE aiming to wiretap information from the SCUs' signals. To enhance PLS, we employ joint artificial noise (AN) and dedicated sensing signal (DSS) in addition to wiretap coding. To evaluate the sensing accuracy, we derive the Cramer-Rao bound (CRB) as a function of the communication, sensing, and AN beamforming (BF) vectors. Subsequently, to assess the PLS level of the ISASC system, we determine a closed-form expression for the semantic secrecy rate (SSR). To achieve an optimal trade-off region between these two competing objectives, we formulate a multi-objective optimization problem for the joint design of the BF vectors. We apply semi-definite programming, Gaussian randomization method, and golden-section search techniques to address this problem. Simulation results demonstrate that the proposed scheme outperforms baseline schemes, achieving a superior trade-off between SSR and CRB.

This paper aims to analyze the stochastic performance of a multiple input multiple output (MIMO) integrated sensing and communication (ISAC) system in a downlink scenario, where a base station (BS) transmits a dual-functional radar-communication (DFRC) signal matrix, serving the purpose of transmitting communication data to the user while simultaneously sensing the angular location of a target. The channel between the BS and the user is modeled as a random channel with Rayleigh fading distribution, and the azimuth angle of the target is assumed to follow a uniform distribution. Due to the randomness inherent in the network, the challenge is to consider suitable performance metrics for this randomness. To address this issue, for users, we employ the user’s rate outage probability (OP) and ergodic rate, while for target, we propose using the OP of the Cramér-Rao lower bound (CRB) for the angle of arrival and the ergodic CRB. We have obtained the expressions of these metrics for scenarios where the BS employs two different beamforming methods. Our approach to deriving these metrics involves computing the probability density function (PDF) of the signal-to-noise ratio for users and the CRB for the target. We have demonstrated that the central limit theorem provides a viable approach for deriving these PDFs. In our numerical results, we demonstrate the trade-off between sensing and communication (S & C) by characterizing the region of S & C metrics and by obtaining the Pareto optimal boundary points, confirmed with simulations.

Random binning is a widely utilized tool in information theory, particularly for proving achievability bounds. In this paper, we investigate the output statistics of random binning (OSRB) for two cases: where the binned sequence is i.i.d. generated, and randomly chosen from an$\epsilon$-typical set using the Tsallis divergence$T_{\alpha}$measure for all values of$\alpha\in(0, \infty)$. For$\alpha=\infty$, due to the unbounded nature of$T_{\infty}$, we analyze the OSRB framework using Rényi's divergence criterion with the order of infinity, denoted as$D_{\infty}$. While exploring OSRB, we encounter a specific form of Renyi's conditional entropy and delve into its properties. Additionally, we demonstrate the effectiveness of this framework in establishing achievability results for wiretap channels, where Tsallis divergence serves as a security measure. The secure rate we obtain is equal to the capacity for$\alpha\in(0.2]$.

Semantic communication is a new paradigm for information transmission that integrates the essential meaning (semantics) of the message into the communication process. However, like in classic wireless communications, the open nature of wireless channels poses security risks for semantic communications. In this paper, we characterize information-theoretic limits for the secure transmission of a semantic source over a wiretap channel. Under separate secrecy and distortion constrains for semantics and observed data, we present general inner and outer bounds on the rate-distortion-equivocation region. We also reduce the general region to the case of Gaussian source and Gaussian wiretap channel and provide numerical evaluations.

In this paper, we propose a cache update policy for wireless networks considering dynamic popularity for file requests. Our network scenario is a wireless network comprised of some cache-equipped access points (APs) which are deployed densely in an area and have connections with core network servers. We model the dynamics of file requests as Markov-modulated Poisson processes. Considering the congestion-dependent delay of APs' services and their overlapping coverage areas, we model the cache service for the cache-missed requests, as a stochastic game in which a Vickrey–Clarke–Groves (VCG) mechanism is exploited at each stage of the game as our proposed file routing policy, and the APs decide independently how to update their caches regarding the routed files. To this end, the APs' utilities are defined based on long-term average file delivery delay including the queueing delay in APs. By finding the Nash equilibrium of the game, we propose policies for both delivery and cache update of dynamic contents. Finally, by comparing numerical results of our proposed scheme with some conventional caching schemes, we show significant improvements in network performance in terms of file delivery delay in different conditions.

In this article, we propose a molecular communication system to localize an abnormality in a diffusion-based medium. We consider a general setup to perform joint sensing, communication, and localization. This setup consists of three types of devices, each for a different task: mobile sensors for navigation and molecule releasing (for communication), fusion centers (FCs) for sampling, amplifying, and forwarding the signal, and a gateway (GW) for making decision or exchanging the information with an external device. The sensors move randomly in the environment to reach the abnormality. We consider both collaborative and noncollaborative sensors that simultaneously release their molecules to the FCs when the number of activated sensors or the moving time reaches a certain threshold, respectively. The FCs amplify the received signal and forward it to the GW for making a decision using either an ideal or a noisy communication channel. A practical application of the proposed model is drug delivery in a tissue of the human body, to guide the nanomachine-bound drug to the exact location and so to eliminate the adverse effects of the drug on normal cells. Further applications are health-care, treatments of localized disease (e.g., tumors and inflammations), immune system triggering, and nanosurgery. The decision rules and probabilities of error are obtained for two considered sensor types in both ideal and noisy communication channels.

In attribute-based access control, users with specific verified attributes will gain access to some particular data. Concerning the privacy of the users’ attributes, we study the problem of distributed attribute-based private access control (DAPAC) with multiple authorities. Each authority will learn and verify only one of the attributes.To investigate its fundamental limits, we introduce an information-theoretic DAPAC framework, with $N \in {\mathbb{N}},N \geq 2$, replicated non-colluding servers (authorities), and some users. Each user has an attribute vector ${{\mathbf{v}}^{\ast}} = \left( {v_1^{\ast}, \ldots,v_N^{\ast}} \right)$ of dimension N and is eligible to retrieve a message ${W^{{{\text{v}}^{\ast}}}}$, available on all servers. Each server n ∈ [N] can only observe and verify the n’th attribute of a user. In response, it sends a function of its authorized messages to the user. The system must satisfy the following conditions: (1) Correctness: the user with attribute vector v*can retrieve his intended message ${W^{{{\text{v}}^{\ast}}}}$ from the servers’ responses, (2) Data Secrecy: the user will not learn anything about the other messages, (3) Attribute Privacy: each Server n learns nothing beyond attribute n of the user. The capacity of the DAPAC is defined as the ratio of the file size and the aggregated size of the responses, maximized over all feasible schemes. We obtain a lower bound on the capacity of this problem by proposing an achievable algorithm with rate $\frac{1}{{2K}}$, where K is the size of the alphabet of each attribute.

Non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) systems are highly efficient. Massive MIMO systems are inherently resistant to passive attackers (eavesdroppers), thanks to transmissions directed to the desired users. However, active attackers can transmit a combination of legitimate user pilot signals during the channel estimation phase. This way they can mislead the base station (BS) to rotate the transmission in their direction, and allow them to eavesdrop during the downlink data transmission phase. In this paper, we analyse this vulnerability in an improved system model and stronger adversary assumptions, and investigate how physical layer security can mitigate such attacks and ensure secure (confidential) communication. We derive the secrecy outage probability (SOP) and a lower bound on the ergodic secrecy capacity, using stochastic geometry tools when the number of antennas in the BSs tends to infinity. We adapt the result to evaluate the secrecy performance in massive orthogonal multiple access (OMA). We find that appropriate power allocation allows NOMA to outperform OMA in terms of ergodic secrecy rate and SOP.

In non-orthogonal multiple access (NOMA) systems, serving multiple users in shared resource blocks can allow untrusted users to overhear the messages of other users. In this context, we study a network consisting of a base station (BS), a near user and a far user, where the latter attempts to overhear the message of the former. The near user is a full-duplex (FD) node that can also act as a relay. Two operating scenarios are considered: 1) friendly jammer (FJ), where the FD node broadcasts noise for degrading the channel between the BS and the far user, while receiving data from the BS; and 2) friendly jammer relay (FJR), where, in addition to degrading the channel between the BS and the far user, the FD node relays the message of the far user. We investigate the secrecy performance of the network by characterizing the secrecy outage probability (SOP) in both scenarios. We obtain the exact SOP of the FJ case, and an approximation for the SOP of the FJR scenario, both expressed in closed-form. Numerical results confirm the accuracy of the analytical results. For a given BS power budget and power allocation to the users, it is demonstrated that the jamming and relaying powers are prominent factors to make the NOMA-FJR scheme superior to NOMA-FJ, as well as to conventional and cooperative NOMA schemes.

In this paper, we study the zero error capacity of the molecular delay channel when multiple molecule types are available at the transmitter. In the molecular delay channel, each transmitted molecule (of any type) is received by a delay of at most $k$ time slots. Depending on the number of molecules that the transmitter is allowed to release in each time slot, we consider the following three cases: (i) when the maximum number of the released molecules of each type in each time slot is restricted (ii) when the total number of the released molecules (regardless of their type) in each time slot is restricted, and (iii) when the transmitter can use only one molecule type (of its choice) in each time slot. We derive lower bounds on the zero-error capacity of the delay channel for each case, by proposing zero-error codes that are based on the results by Kovačević and Popovski. We also derive upper bounds on the zero-error capacity of the delay channel. In the first case, these bounds match and yield the exact capacity, while in the other two cases, the bounds are shown to be close numerically. Our numerical results show that as the number of available molecule types increases, the capacity of the system increases substantially, compared to using only one molecule type. Furthermore, it is shown that the lower and upper bounds on the zero-error capacity of the delay channel in the second case are generally close to the lower and upper bounds in the third case, respectively, indicating the closeness of the zero-error capacities of the two cases. This result enables one to design a simpler system by employing a high rate code that has only one molecule type in each slot (designed for the third case) in the channel of the second case, without much rate loss.

In this paper, we argue that in many basic algorithms for machine learning, including support vector machine (SVM) for classification, principal component analysis (PCA) for dimensionality reduction, and regression for dependency estimation, we need the inner products of the data samples, rather than the data samples themselves.Motivated by the above observation, we introduce the problem of private inner product retrieval for distributed machine learning, where we have a system including a database of some files, duplicated across some non-colluding servers. A user intends to retrieve a subset of specific size of the set of the inner product of every pair of data items in the database with minimum communication load, without revealing any information about the identity of the requested subset. For achievability, we use the algorithms for multi-message private information retrieval. For converse, we establish that as the length of the files becomes large, the set of all inner products converges to independent random variables with uniform distribution hence we find asymptotic capacity for this problem. We also derive the rate of this convergence. To prove that, we construct special dependencies among sequences of the sets of all inner products with different length, which forms a time-homogeneous irreducible Markov chain, without affecting the marginal distribution. We show that this Markov chain has a uniform distribution as its unique stationary distribution, with rate of convergence dominated by the second largest eigenvalue of the transition probability matrix. This allows us to develop a converse, which converges to a tight bound in some cases, as the size of the files becomes large.

The main security service in the connected world of cyber physical systems necessitates to authenticate a large number of nodes privately. In this paper, the private authentication problem is considered, that consists of a certificate authority, a verifier, many legitimate users (prover) and any arbitrary number of illegitimate users. Each legitimate user wants to be authenticated (using his personal key) by the verifier, while simultaneously wants to stay completely anonymous (even to the verifier and the CA). On the other hand, an illegitimate user must fail to authenticate himself. We analyze this problem from an information theoretical perspective. First, we propose a general interactive information-theoretic model for the problem. As a metric to measure the reliability, we consider the authentication key rate whose rate maximization has a trade-off with establishing privacy. Then, we analyze the problem in two different regimes: 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). For both regimes, we propose schemes that satisfy the completeness, soundness and privacy properties. In finite size regime, the idea is to generate the authentication keys according to a secret sharing scheme. In asymptotic regime, we use a random binning based scheme which relies on the joint typicality to generate the authentication keys. Moreover, providing the converse proof, we show that our scheme achieves capacity in the asymptotic regime. For finite size regime our scheme achieves capacity for large field size.

Chemical reactions are a prominent feature of molecular communication systems, with no direct parallels in wireless communications. While chemical reactions may be used inside the transmitter nodes, receiver nodes, or the communication medium, we focus on its utility in the medium in this paper. Such chemical reactions can be used to perform computation over the medium as molecules diffuse and react with each other (physical-layer computation). We propose the use of chemical reactions for the following purposes: 1) to reduce signal-dependent observation noise of receivers by reducing the signal density; 2) to realize molecular physical-layer network coding (PNC) by performing the natural XOR operation inside the medium; and 3) to reduce the inter-symbol interference (ISI) of other transmitters by canceling out the remaining molecules from previous transmissions. To make the ideas formal, we consider an explicit two-way relaying example with a transparent receiver (which has a signal-dependent noise). The proposed ideas are used to define a modulation scheme (which we call the PNC scheme). We compare the PNC with a previously proposed scheme for this problem, where the XOR operation is performed at the relay node (using a molecular logic gate). We call the latter, the straightforward network coding (SNC). It is observed that in addition to the simplicity of the proposed PNC scheme, it outperforms the SNC scheme especially when we consider ISI.

While ISI is a common issue in classical communications, it is more challenging and prominent in the context of molecular communication, because one cannot readily combat ISI with classical channel equalization techniques. This is due to the fact that transmitter can only release a positive amount of concentration of a specific molecule into the medium. Previous works have proposed use of chemical reactions to remove molecules from the environment, and to effectively simulate negative signals. However, the differential equation describing a diffusion-reaction process is non-linear. This precludes the possibility of using Fourier transform tools. In this paper, a solution for simulating negative signals based on the diffusion-reaction channel model is proposed. While the proposed solution does not exploit the full degrees of freedom available for signaling in a diffusion-reaction process, but its end-to-end system is a linear channel and amenable to Fourier transform analysis. Based on our solution, a modulation scheme and a precoder are introduced and shown to have a significant reduction in error probability compared with previous modulation schemes, such as concentration shift keying (CSK), pre-equalization, depleted-molecule shift keying (D-MoSK), and molecular concentration shift keying (MCSK). The effects of various imperfections (such as quantization error) on the communication system performance are studied.

In some applications, the variance of additive measurement noise depends on the signal that we aim to measure. For instance, additive signal-dependent Gaussian noise (ASDGN) channel models are used in molecular and optical communication. Herein, we provide lower and upper bounds on the capacity of additive signal-dependent noise (ASDN) channels. The first lower bound is based on an extension of majorization inequalities, and the second lower bound utilizes the properties of the differential entropy. The lower bounds are valid for arbitrary ASDN channels. The upper bound is based on a previous idea of the authors (“symmetric relative entropy”) and is applied to the ASDGN channels. These bounds indicate that in the ASDN channels (unlike the classical additive white Gaussian noise channels), the capacity does not necessarily become larger by reducing the noise variance function. We also provide sufficient conditions under which the capacity becomes infinite. This is complemented by some conditions implying that the capacity is finite, and a unique capacity achieving measure exists (in the sense of the output measure).

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interference-limited communications considered in prior works, we propose active cooperative relaying-based schemes. We consider a network with nl legitimate nodes, ne eavesdroppers, and path loss exponent α ≥ 2. As long as ne2(log(ne))γ= o(nl), for some positive γ, we show that one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given fixed total power constraint for the entire network. We achieve this result through: 1) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays and 2) the relays acting as a virtual multi-antenna to apply beamforming against the eavesdroppers. Our simpler parallel (two-stage) relaying scheme can achieve the same unbounded secure aggregate rate when neα/2+1(log(ne))γ +δ(α/2+1)= o(nl) holds, for some positive γ, δ. Finally, we study the improvement (to the detriment of legitimate nodes) that the eavesdroppers achieve in terms of the information leakage rate in a large cooperative network in the case of collusion. We show that again the zero-cost secure communication is possible, if ne(2+2/α)(log ne)γ= o(nl) holds, e for some positive γ; that is, in the case of collusion slightly fewer eavesdroppers can be tolerated compared with the non-colluding case.

In this paper, we propose a new packet prioritization scheme in order to exploit the full-duplex (FD) capability of the access point (AP) more efficiently, in an asymmetric IEEE 802.11-based WLAN, i.e., only the AP has the in-band FD communications capability. In this respect, we consider a modified version of IEEE 802.11 MAC protocol such that at any transmission opportunity in which AP has the role of the transmitter or the receiver, it does the best to select a partner packet to be simultaneously received or transmitted, respectively. The key feature of our proposed partner packet selection scheme is to reduce the idle time intervals that in an FD transmission opportunity, due to different transmission times of the packet and its partner usually exist. To this end, we consider the packet lengths, the waiting time of the packets as well as the interfering effects of the two simultaneously active links on each other as the effective factors in prioritizing the packets to be selected as the partner. We map the problem onto finding a two-sided stable many-to-many matching table. Our numerical results indicate the high efficiency of the proposed scheme in exploiting the time, i.e., decreasing idle time intervals as well as increasing the throughput at the cost of controlled relaxation of the average delay.

In this paper, we propose a data offloading algorithm in a network comprised of a macro base station and a few number of WiFi access points with overlapped coverage areas. The main goal of our algorithm is how to assign offloaded mobile stations (MSs) to access points (APs). Our approach in proposing the algorithm is based on mapping the problem onto finding a suitable matching algorithm, in order to minimize the average delay of the offloaded packets as one of the main QoS parameters on the one hand and to maximize the utility of the APs on the other hand. The utility of each AP is considered to be a combination of monetary benefit due to offloading service and the cost due to extra energy consumption. Since the preferences over APs from the viewpoint of MSs are dependent on each other, our problem is in fact a matching problem with externalities. Thus, in order to obtain a suitable matching, we apply swap matching algorithm to reach a final matching satisfying two-sided exchange stability. Our numerical results show the superiority of our proposed algorithm when compared to two simple assigning algorithms based on maximum SNR and traffic load balancing.

Energy harvesting has been developed as an effective technology for communication systems in order to extend their lifetime. In this paper, we consider a single-user energy harvesting wireless communication system, in which arrival data and harvested energy curves are modeled as continuous functions. 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. We find this optimal algorithm, by showing its properties. Next, we propose an online algorithm for this system and obtain its performance bound.

In this paper, we consider the bacterial point-to-point communication problem with one transmitter and one receiver by considering the ligand receptor binding process. The most commonly investigated signalling model, referred to as the Level Scenario (LS), uses one type of a molecule with different concentration levels for signaling. An alternative approach is to employ multiple types of molecules with a single concentration level, referred to as the Type Scenario (TS). We investigate the trade-offs between the two scenarios for the ligand receptor from the capacity point of view. For this purpose, we evaluate the capacity using numerical algorithms. Moreover, we derive an upper bound on the capacity of the ligand receptor for a Binomial Channel (BIC) model, using symmetrized Kullback-Leibler (KL) divergence. A lower bound is also derived when the environment noise is negligible. Finally, we analyse the effect of blocking of a receptor by a molecule of a different type, by proposing a new Markov model in the multiple-type signalling.

The authors propose a new technique to model the arriving energy's knowledge (AEK) in the energy harvesting (EH) communication systems. They consider a batteryless EH transmitter with the AEK non‐causally provided to it. They show that the capacity of the authors' model in general case, that is, discrete memoryless channel, can be derived through a binning scheme. This resembles a Gelfand–Pinsker type capacity formula which intuitively is the result of treating the energy as a channel state. Moreover, they investigate two especial cases of binary and Gaussian channels with the EH transmitters. In the binary symmetric channel with EH transmitter (BSCEH), their coding scheme leads to achieve the capacity of the classic binary symmetric channel (BSC). In the batteryless Gaussian channel with EH transmitter, the upper bound on the capacity is derived, and it is shown this bound is less than the capacity of the EH Gaussian channel with infinite battery.

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interference-limited communications considered in prior works, we propose active cooperative relaying based schemes. We consider a network with nllegitimate nodes and neeavesdroppers, and path loss exponent α ≥ 2. As long as ne2(log(ne))γ= o(nl) holds for some positive γ, we show one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given a fixed total power constraint for the entire network. We achieve this result with (i) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays, and (ii) the relays acting as a virtual multi-antenna to apply beamforming against the eavesdroppers. Our simpler parallel (two-stage) relaying scheme can achieve the same unbounded secure aggregate rate when neα/2 + 1(log(ne))γ+δ(α/2+1)= o(nl) holds, for some positive γ, δ.

We investigate the problem of reliable communication in the presence of active adversaries that can tamper with the transmitted data. We consider a legitimate transmitter-receiver pair connected over multiple communication paths (routes). We propose two new models of adversary, a “memoryless” and a “foreseer” adversary. For both models, the adversaries are placing themselves arbitrarily on the routes, keeping their placement fixed throughout the transmission block. This placement may or may not be known to the transmitter. The adversaries can choose their best modification strategy to increase the error at the legitimate receiver, subject to a maximum distortion constraint. We investigate the communication rates that can be achieved in the presence of the two types of adversaries and the channel (benign) stochastic behavior. For memoryless adversaries, the capacity is derived. Our method is to use the typical set of the anticipated received signal for all possible adversarial strategies (including their best one) in a compound channel that also captures adversarial placement. For the foreseer adversaries, which have enhanced observation capabilities compared to the memoryless ones, we propose a new coding scheme to guarantee resilience, i.e., recovery of the codeword independently of the adversarial (best) choice. We derive an achievable rate and we propose an upper bound on the capacity. We evaluate our general results for specific cases (e.g., binary symbol replacement or erasing attacks), to gain insights.

In this study, the three‐user interference channel (IFC) with common information is considered, where each receiver decode not only the private message from the intended transmitter but also the common messages from the non‐intended transmitters by applying a simultaneous decoding scheme. An achievable rate region is presented using rate splitting and superposition encoding at the transmitters and simultaneous joint decoding at the receivers in which the transmitters cooperatively send the split messages which allows the interference cancellation at the receivers. The implicit form of the achievable rate region is also extended to K ‐user IFC with common information. Finally the inner bound derived for the three‐user discrete memoryless IFC with common information is generalised to the Gaussian case and is evaluated in a numerical example.

Energy harvesting (EH) has emerged as a promising technique for Green Communications and it is a novel technique to prolong the lifetime of the wireless networks with replenishable nodes. In this study, the authors consider the energy shortage analysis of fixed rate transmission in communication systems with EH nodes. First, the authors study the finite‐horizon transmission and provide the general formula for the energy shortage probability (ESP). The authors also give some examples as benchmarks. Then, the authors continue to derive a closed‐form expression for infinite‐horizon transmission, which is a lower bound for the ESP of any finite‐horizon transmission. These results are proposed for both Additive White Gaussian Noise (AWGN) and fading channels. Moreover, the authors show that even under random energy arrival , one can transmit at a fixed rate equal to capacity in the AWGN channels with negligible aggregate shortage time. The authors achieve this result using our practical transmission schemes, proposed for finite‐horizon. Also, comprehensive numerical simulations are performed in AWGN and fading channels with no Channel State Information (CSI) available at the transmitter, which corroborate our theoretical findings. Furthermore, the authors improve the performance of our transmission schemes in the fading channel with no CSI at the transmitter by optimising the transmission initiation threshold.

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 discussed in which a distributed doubly symmetric binary source is available.

In this paper, we study the one-receiver two-eavesdropper Broadcast Channel (BC) with three degraded message sets. A common message is sent to three receivers. Another message is sent to the first and second receivers and needs to be kept secret from the third receiver (second eavesdropper). The third message is sent to the first receiver and needs to be kept secret from the second and third receivers (first and second eavesdroppers). First, we consider perfect secrecy conditions at the eavesdroppers, where we find an achievable perfect secrecy region. In the achievability scheme, we use superposition coding which divides the available randomness into different levels. These levels are used to mislead the eavesdroppers. The proposed coding scheme determines the perfect secrecy capacity region of the one-receiver two-eavesdropper BC with three degraded message sets, when the receivers exhibit a degradedness order. Next, we find an achievable rate-equivocation region using the rate splitting technique and indirect decoding. We show that for the two-receiver one-eavesdropper BC with three degraded message sets where we relax the secrecy condition at the second receiver, our coding scheme is optimal when the second receiver is a degraded version of the first receiver and it is less noisy than the third receiver.

This paper introduces a new applicable Gaussian wiretap channel with side information. In this channel, the state of the channel to the wiretapper is separated from the main channel's one. It means that the legitimate receiver and the wiretapper are listening to the transmitted signal through the different channels with different channel states which may have some correlation to each other. The state of the main channel, is assumed to be known at the transmitter, helps the sender to encrypt its messages. The achievable equivocation-rate region for this model is drived in the Gaussian case and the results are reduced to the previous works as special cases.

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 characterised. 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.

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 noncausal generalized feedback. For this purpose, we introduce the causal C-IFC with delay (CC-IFC-WD) in which the cognitive user's transmission can depend onLfuture 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 ofLand 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 noncausally knows its entire received sequence. In each case, we obtain a new inner bound on the capacity region. The derived achievable rate regions under special conditions reduce to several previously known results. 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 semideterministic 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 show that one can achieve larger rate regions in the “without delay” and “unlimited look-ahead” cases than in the classical CC-IFC; this improvement is likely due to the fact that, in the former two cases, the cognitive user can cooperate more effectively with the primary user by knowing the current and future received symbols.

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.

In this paper, we introduce discrete memoryless Interference Channel (IFC) with two relays as two interfering transmitter-receiver pairs that are aided by two relays. We propose two different coding strategies for this channel. In the first strategy, we assume that each relay tries to mainly help one of the transmitter-receiver pairs through signal relaying and interference cancellation, while in the second strategy we assume that each relay tries to help both transmitter-receiver pairs. In our coding schemes, we employ rate-splitting, generalized block Markov coding, superposition coding and Gel'fand-Pinsker binning to cancel parts of the interference known to be experienced at the receivers. The derived achievable rate regions can be specialized to new achievable rate regions for discrete memoryless IFC with a relay. Under special conditions, the derived achievable rate regions also reduce to some previously known ones.transmitter-receiver pairs.

In this paper, we investigate Causal Cognitive Interference Channel (CC-IFC) with delay in which the cognitive user transmission can depend on L future received symbols as well as the past ones. We study two special cases: CC-IFC without delay (L = 1), where the cognitive user can use only current and past received symbols, and CC-IFC with a block length delay (L = n), wherein the entire received sequence can be used. In each case, we obtain an inner bound on the capacity region. Our coding schemes are based on the generalized block Markov superposition coding and instantaneous relaying for CC-IFC without delay, and non-causal partial Decode-and-Forward (DF) for CC-IFC with a block length delay. Further, providing converse proofs, we show that the derived inner bounds are tight in some cases. Hence, we characterize the capacity regions for the classes of degraded and semi-deterministic CC-IFC without delay and CC-IFC with a block length delay, under strong interference conditions.

The discrete memoryless state-dependent relay channel (SD-RC) is considered in this study. Two main cases are investigated: SD-RC with non-causal channel state information (CSI) and SD-RC with causal CSI. In each case, the SD-RC with partial CSI at the source and the relay is considered. As special cases it includes three different situations in which perfect CSI is available: (i) only at the source, (ii) only at the relay and (iii) both at the source and the relay. For the non-causal situation, the authors establish lower bound on capacity (achievable rate) of the SD-RC, using Gel'fand-Pinsker coding at the nodes informed of CSI and compress-and-forward (CF) strategy at the relay. Using the Shannon's strategy and CF relaying, the authors derive lower bound on capacity of SD-RC in the causal case. Furthermore, in order to compare their derived bounds with the previously obtained results, which are based on the decode-and-forward (DF) strategy, the authors consider general Gaussian relay channel (RC) with additive independent and identically distributed Gaussian state and noise, and obtain lower bounds on capacity for the cases in which perfect CSI is available non-causally at the source or at the relay. They also present cases in which their lower bounds outperform DF-based bounds, and can achieve rates close to the upper bound. For causal case, a numerical example of the binary fading Gaussian RC with additive noise is provided.

In this paper, we consider a discrete memoryless state-dependent relay channel with non-causal channel state information (CSI). We investigate three different cases in which perfect channel states can be known non-causally: (i) only to the source, (ii) only to the relay or (iii) both to the source and to the relay node. For these three cases we establish lower bounds on the channel capacity (achievable rates) based on using Gel'fand-Pinsker coding at the nodes where the CSI is available and using compress-and-forward (CF) strategy at the relay. Furthermore, for the general Gaussian relay channel with additive independent and identically distributed (i.i.d) states and noise, we obtain lower bounds on the capacity for the cases in which CSI is available at the source or at the relay. We also compare our derived bounds with the previously obtained results which were based on decode-and-forward (DF) strategy, and we show the cases in which our derived lower bounds outperform DF based bounds, and can achieve the rates close to the upper bound.

In this paper, we consider partially and fully cooperative state-dependent relay broadcast channels with perfect causal channel state information (CSI). For these two channels, we study three different situations: 1) both the source and the relay nodes have access to perfect CSI, 2) perfect CSI is only known to the relay nodes, 3) perfect CSI is only available at the source node. In each situation we obtain the capacity region for a degraded version of the channel. Our work subsumes previously obtained results for the degraded broadcast and relay channels with perfect causal CSI.

We investigate the parallel partially cooperative relay broadcast channel with unmatched degraded subchannels. We characterize the capacity region of this channel in the general setting that, transmitter sends a common message for both users and a private message for each of them. Our achievability result is based on the choosing appropriate parameters for the general achievable rate region of partially cooperative relay broadcast channel. We provide a converse proof for this achievable region as well, which establishes the capacity region.

In this paper we prove a new capacity upper bound for a class of relay channels known as Relay-With-Delay channels. The proposed bound is general and holds for any arbitrary amount of delay. We have shown that the previously introduced bounds can be considered as special cases of our proposed upper bound. The new introduced bound is, in some cases, tighter than the previously established bounds. It is also notable that the proposed bound coincides with the previously known capacity of ¿Relay-With-Delay¿ channels.