Next-generation wireless networks are progressing beyond conventional connectivity to incorporate emerging sensing and computing capabilities. This convergence gives rise to integrated systems that enable not only uninterrupted communication, but also environmental awareness, intelligent decision-making, and novel applications that take advantage of these combined features. At the same time, this integration brings substantial security challenges. As computing, sensing, and communication become more tightly intertwined, the overall complexity of the system increases, creating new vulnerabilities and expanding the attack surface. The widespread deployment of data-heavy artificial intelligence applications further amplifies concerns regarding data security and privacy. This paper presents a comprehensive survey of security and privacy threats, along with potential countermeasures, in integrated wireless systems. We first review physical-layer security techniques for communication networks, and then investigate the security and privacy implications of semantic and pragmatic communications and their associated cross-layer design methodologies. For sensing functionalities, we pinpoint security and privacy risks at the levels of signal sources, propagation channels, and sensing targets, and summarize state-of-the-art defense strategies for each. The growing computational requirements of these applications drive the need for distributed computing over the network, which introduces additional risks such as data leakage, weak authentication, and multiple points of failure. We subsequently discuss secure coded computing approaches that can help overcome several of these challenges. Finally, we introduce unified security frameworks tailored to integrated communication–sensing–computing architectures, offering an end-to-end perspective on protecting future wireless systems.

We study finite-state finite-action Bayesian statistical decision problems. While exact error-exponent characterizations are known for several special cases, including hypothesis testing and hypothesis exclusion, the asymptotic behavior of the optimal Bayes regret is largely unknown for general decision problems. In this paper, we show that the optimal regret always decays exponentially fast and characterize its exact exponent for arbitrary loss functions. The exponent is given by the minimum multivariate Chernoff information over the minimal incompatible subsets of states, where an incompatible subset is a collection of states for which no single action is optimal for all states in the subset. Our result recovers the classical pairwise-minimum Chernoff exponent for symmetric multiple hypothesis testing and the multivariate Chernoff exponent for hypothesis exclusion, while also yielding, to the best of our knowledge, the first exact exponent characterization for list hypothesis testing.

We study the problem of discrete distribution estimation under utility-optimized local differential privacy (ULDP), which enforces local differential privacy (LDP) on sensitive data while allowing more accurate inference on non-sensitive data. In this setting, we completely characterize the fundamental privacy–utility trade-off. The converse proof builds on several key ideas, including a generalized uniform asymptotic Cramér–Rao lower bound, a reduction showing that it suffices to consider a newly defined class of extremal ULDP mechanisms, and a novel distribution decomposition technique tailored to ULDP constraints. For the achievability, we propose a class of utility-optimized block design (uBD) schemes, obtained as nontrivial modifications of the block design mechanism known to be optimal under standard LDP constraints, while incorporating the distribution decomposition idea used in the converse proof and a score-based linear estimator. These results provide a tight characterization of the estimation accuracy achievable under ULDP and reveal new insights into the structure of optimal mechanisms for privacy-preserving statistical inference.

Federated ensemble distillation addresses client heterogeneity by generating pseudo-labels for an unlabeled server dataset based on client predictions and training the server model using the pseudo-labeled dataset. The unlabeled server dataset can either be pre-existing or generated through a data-free approach. The effectiveness of this approach critically depends on the method of assigning weights to client predictions when creating pseudo-labels, especially in highly heterogeneous settings. Inspired by theoretical results from GANs, we propose a provably near-optimal weighting method that leverages client discriminators trained with a server-distributed generator and local datasets. Our experiments on various image classification tasks demonstrate that the proposed method significantly outperforms baselines. Furthermore, we show that the additional communication cost, client-side privacy leakage, and client-side computational overhead introduced by our method are negligible, both in scenarios with and without a pre-existing server dataset.

For multiple hypothesis testing based on classical data samples, we demonstrate a quantum advantage in the optimal privacy-utility trade-off (PUT), where the privacy and utility measures are set to (quantum) local differential privacy and the pairwise-minimum Chernoff information, respectively. To show the quantum advantage, we consider some class of hypotheses that we coin smoothed point masses. For such hypotheses, we derive an upper bound of the optimal PUT achieved by classical mechanisms, which is tight for some cases, and propose a certain quantum mechanism which achieves a better PUT than the upper bound. The proposed quantum mechanism consists of a classical-quantum channel whose outputs are pure states corresponding to a symmetric informationally complete positive operator-valued measure (SIC-POVM), and a depolarizing channel.

This study explores an uplink multi-users covert communication system where certain users cooperate to hide messages from a covert user. A recent work investigated the multi-users covert communication system in which all the users are located at an equal distance from the legitimate receiver and a warden. In contrast, our work extends the existing work to an unequal distance scenario, where users are at unequal distances from the legitimate receiver. In particular, we establish that an on-off scheme, previously proven to be optimal in the equal distance scenario, remains optimal in the unequal distance scenario. The optimality of the on-off scheme enables us to derive expressions of the minimum detection error probability and outage probability in closed-forms. In addition, the closed-form expressions allow us to turn the parameter optimization into a simple one-dimensional search problem. Finally, the theoretical results developed in this work are validated by comparing extensive performance evaluations utilizing the theoretical results and Monte Carlo simulations.

We consider a discrete distribution estimation problem under a local differential privacy (LDP) constraint in the presence of shared randomness. For this problem, we propose a new class of LDP schemes achieving the exactly optimal privacy-utility trade-off (PUT), with the communication cost less than or equal to the size of the input data. Moreover, it is shown as a simple corollary that one-bit communication is sufficient for achieving the exactly optimal PUT for a high privacy regime if the size of the input data is an even number. The main idea is to decompose a block design scheme proposed by Park et al. (2023), based on the combinatorial concept called resolution. We call the resultant decomposed LDP scheme with shared randomness as a resolution of the original block design scheme. A resolution of a block design scheme has a communication cost less than or equal to that of the original block design scheme. Also, the resolution of a block design scheme is exactly optimal whenever the original block design scheme is exactly optimal. Accordingly, we provide a resolution of the exactly optimal subset selection scheme proposed by Ye and Barg (2018), called the Baranyai's resolution. The Baranyai's resolution is not only exactly optimal, but also it achieves the minimum communication cost among all exactly optimal resolutions of block design schemes.

We consider a private discrete distribution estimation problem with one-bit communication constraint. The privacy constraints are imposed with respect to the local differential privacy. The estimation error is quantified by the worst-case mean squared error. We completely characterize the first-order asymptotics of this privacy-utility trade-off under the one-bit communication constraint by using ideas from local asymptotic normality and the resolution of a block design mechanism. This results demonstrate the optimal dependence of the privacy-utility trade-off under the one-bit communication constraint in terms of the privacy constraint and the size of the alphabet of the discrete distribution.

In this paper, we show that there is no advantage of using non-local cooperation between source encoders in improving the optimal compression rate (or rate region) for some canonical distributed compression tasks. The tasks are the lossless distributed compression, the lossless compression with a helper, and some special cases of the lossy distributed compression for 2-component discrete memoryless sources. These negative results for distributed source coding contrast with those for multi-user channel coding: quantum or general no-signaling cooperation between channel encoders improves the capacity region for some multiple access and interference channels.

The sampling problem under local differential privacy has recently been studied with potential applications to generative models, but a fundamental analysis of its privacy-utility trade-off (PUT) remains incomplete. In this work, we define the fundamental PUT of private sampling in the minimax sense, using the $f$-divergence between original and sampling distributions as the utility measure. We characterize the exact PUT for both finite and continuous data spaces under some mild conditions on the data distributions, and propose sampling mechanisms that are universally optimal for all $f$-divergences. Our numerical experiments demonstrate the superiority of our mechanisms over baselines, in terms of theoretical utilities for finite data space and of empirical utilities for continuous data space.

In this work, we study a covert communication scheme in which some users are opportunistically selected to emit interference signals for the purpose of hiding the communication of a covert user. This work reveals interesting facts that the channel correlation is beneficial to the throughput of the covert communication but detrimental to the energy efficiency, which has never been discussed before. The study is conducted in a generic setup where the channels between pairs of entities in the scheme are correlated. For the setup, we discover that the optimal power profile of the interference signals from the selected users turns out to be the equal power transmission at their maximum transmit power level. In addition, we optimize system parameters of the scheme for maximizing throughput and energy efficiency utilizing$Q$-learning, which however is plagued with long learning time and large storage space when the dimension of state gets large and/or a fine resolution of reward function value is necessary. To resolve the technical challenge, we propose a scalable$Q$-learning which recursively narrows down the discretization level of the continuous state in an iterative fashion. To confirm the results in this work, the system parameters are evaluated with theoretical results for independent channels and compared with the ones from the proposed scalable$Q$-learning.

We consider a private discrete distribution estimation problem with one-bit communication constraint. The privacy constraints are imposed with respect to the local differential privacy and the maximal leakage. The estimation error is quantified by the worst-case mean squared error. We completely characterize the first-order asymptotics of this privacy-utility trade-off under the one-bit communication constraint for both types of privacy constraints by using ideas from local asymptotic normality and the resolution of a block design mechanism. These results demonstrate the optimal dependence of the privacy-utility trade-off under the one-bit communication constraint in terms of the parameters of the privacy constraint and the size of the alphabet of the discrete distribution.

We consider a discrete distribution estimation problem under a local differential privacy (LDP) constraint in the presence of shared randomness. For this problem, we propose a new class of LDP schemes achieving the exactly optimal privacy-utility trade-off (PUT), with the communication cost less than or equal to the size of the input data. Moreover, it is shown as a simple corollary that one-bit communication is sufficient for achieving the exactly optimal PUT for a high privacy regime if the input data size is an even number. The main idea is to decompose a block design scheme proposed by Park et al. (2023), based on the combinatorial concept called resolution. We call the resultant decomposed LDP scheme with shared randomness as a resolution of the original block design scheme. A resolution of a block design scheme has a communication cost less than or equal to that of the original block design scheme. Also, the resolution of a block design scheme is exactly optimal whenever the original block design scheme is exactly optimal. Accordingly, we provide two resolutions of the exactly optimal subset selection scheme proposed by Ye and Barg (2018), called the Baranyai’s resolution and the cyclic shift resolution. We show that the Baranyai’s resolution achieves the minimum communication cost among all exactly optimal resolutions of block design schemes. One drawback of the Baranyai’s resolution is that its explicit structure is unknown in general. In contrast, the cyclic shift resolution has an explicit structure, but its communication cost can be larger than that of the Baranyai’s resolution. To complement this, we also suggest resolutions of other block design schemes achieving the exactly optimal PUT for some input data size and privacy budget. Those require the minimum communication cost as the Baranyai’s resolution and have explicit structures as the cyclic shift resolution.

In this paper, we propose a new class of local differential privacy (LDP) schemes based on combinatorial block designs for a discrete distribution estimation. This class not only recovers many known LDP schemes in a unified framework of combinatorial block design, but also suggests a novel way of finding new schemes achieving the optimal (or near-optimal) privacy-utility trade-off with lower communication costs. Indeed, we find many new LDP schemes that achieve both the optimal privacy-utility trade-off and the minimum communication cost among all the unbiased schemes for a certain set of input data size and LDP constraint. Furthermore, to partially solve the sparse existence issue of block design schemes, we consider a broader class of LDP schemes based on regular and pairwise-balanced designs, called RPBD schemes, which relax one of the symmetry requirements on block designs. By considering this broader class of RPBD schemes, we can find LDP schemes achieving near-optimal privacy-utility trade-off with reasonably low communication costs for a much larger set of input data size and LDP constraint.

In this paper, we address the problem of path planning for a cellular-enabled UAV with connectivity and battery constraints. The UAV’s mission is to deliver a payload from an initial point to a final point, while maintaining connectivity with a BS and adhering to the battery constraint. The UAV’s battery can be replaced by a fully charged battery at a charging station, which takes some time. Our key contribution lies in proposing an algorithm that efficiently computes an optimal path that minimizes the mission completion time, solvable in polynomial time. We achieve this by transforming the problem into an equivalent two-level shortest path finding problem over weighted graphs and leveraging graph theoretic approaches to solve it. In more detail, we first find an optimal path and speed to travel between each pair of charging stations without replacing the battery, and then find the optimal order of visiting charging stations. To demonstrate the effectiveness of our approach, we compare it with previously proposed algorithms and show that our algorithm outperforms those in terms of both computational complexity and performance.

For multi-band wireless ad hoc networks of multiple users, an anti-jamming game between the users and a jammer is studied. In this game, the users (resp. jammer) want to maximize (resp. minimize) the expected rewards of the users taking into account various factors such as communication rate, hopping cost, and jamming loss. We analyze the arms race of the game and derive an optimal frequency hopping policy at each stage of the arms race based on the Markov decision process (MDP). It is analytically shown that the arms race reaches an equilibrium after a few rounds, and a frequency hopping policy and a jamming strategy at the equilibrium are characterized. We propose two kinds of collision avoidance protocols to ensure that at most one user communicates in each frequency band, and provide various numerical results that show the effects of the reward parameters and collision avoidance protocols on the optimal frequency hopping policy and the expected rewards at the equilibrium. Moreover, we discuss about equilibria for the case where the jammer adopts some unpredictable jamming strategies.

This work studies a covert communication scheme for an uplink multi-user scenario in which some users are opportunistically selected to help a covert user. In particular, the selected users emit interfering signals via an orthogonal resource dedicated to the covert user together with signals for their own communications using orthogonal resources allocated to the selected users, which helps the covert user hide the presence of the covert communication. For the covert communication scheme, we carry out extensive analysis and find system parameters in closed forms. The analytic derivation for the system parameters allows one to find the optimal combination of system parameters by performing a simple one-dimensional search. In addition, the analytic results elucidate relations among the system parameters. In particular, it will be proved that the optimal strategy for the non-covert users is an on-off scheme with equal transmit power. The theoretical results derived in this work are confirmed by comparing them with numerical results obtained with exhaustive searches. Finally, we demonstrate that the results of work can be utilized in versatile ways by demonstrating a design of covert communication with energy efficiency into account.

We consider a discrete distribution estimation problem under the local differential privacy and the one-bit communication constraints. A fundamental privacy-utility tradeoff in this problem is formulated as the minimax squared loss. We show a tighter lower bound on the minimax squared loss, which has exactly the same form with the upper bound by the recursive Hadamard response by Chen et al. up to a constant factor of 4 for arbitrary LDP constraint and arbitrary finite data space. To derive the lower bound, we modify the van Trees inequality to involve a symmetrized Fisher information, which is invariant under the choice of the coordinate system on the probability simplex. We further characterize the maximum of the symmetrized Fisher information by considering the joint effect of the privacy and the communication constraints.

We consider a complex Gaussian wiretap channel with finite-resolution analog-to-digital converters (ADCs) at both the legitimate receiver and the eavesdropper. For this channel, we show that a positive secrecy rate is always achievable as long as the channel gains at the legitimate receiver and at the eavesdropper are different, regardless of the quantization levels of the ADCs. For the achievability, we first consider the case of the one-bit ADCs at the legitimate receiver and apply a binary input distribution where the two input points have the same phase when the channel gain at the legitimate receiver is less than that at the eavesdropper, and otherwise the opposite phase. Then the result is generalized for the case of arbitrary finite-resolution ADCs at the legitimate receiver by translating the input distribution appropriately. We also provide numerical lower bounds on the achievable secrecy rates, and analyze the tendency of the secrecy rates according to the channel difference, the power constraint, and the quantization levels for some cases. For the special case of the real Gaussian wiretap channel with one-bit ADCs at both the legitimate receiver and the eavesdropper, we show that our choice of phase does not lose any optimality for the Wyner code.

We study the covert communication over K-user-pair discrete memoryless interference channels (DM-ICs) with a warden. It is assumed that the warden's channel output distribution induced by K “off” input symbols, which are sent when no communication occurs, is not a convex combination of those induced by any other combination of input symbols (otherwise, the square-root law does not hold). We derive the exact covert capacity region and show that a simple point-to-point based scheme with treating interference as noise is optimal. In addition, we analyze the secret key length required for the reliable and covert communication with the desired rates, and present a channel condition where a secret key between each user pair is unnecessary. The results are extended to the Gaussian case and the case with multiple wardens.

We study the effect of node mobility on the throughput scaling of the covert communication over a wireless adhoc network. It is assumed that n mobile nodes want to communicate each other in a unit disk while keeping the presence of the communication secret from each of Θ(ns) non-colluding wardens (s > 0). The wardens can be mobile or fixed. Our results show that the node mobility greatly improves the throughput scaling, compared to the case of fixed node location. In particular, for s ≤ 1, the aggregate throughput scaling, i.e., the maximally achievable throughput scaling of the total network when each source-destination pair communicates with the same rate, is shown to be arbitrarily close to linear in n when the number of channel uses l that each warden uses to judge the presence of communication is not too large compared to n. More specifically, the aggregate throughput scaling is arbitrarily close to linear when s ≤ 1 and l = O(n(α-2)(1-s)), where α ≥ 2 denotes the path loss exponent. For the achievability, we modify the two-hop based scheme by Grossglauser and Tse (2002), which was proposed for a wireless ad hoc network without a covertness constraint, by introducing a preservation region around each warden in which the senders are not allowed to transmit and by carefully analyzing the effect of covertness constraint on the transmit power and the resultant transmission rates. This scheme is shown to be optimal for 0 <; s ≤ 1 under an assumption that each node outside preservation regions around wardens uses the same transmit power.

In this paper, the covert communication scenario over K-user-pair discrete memoryless interference channels with a warden is studied. We assume that the wardens channel output distribution induced by K "off input symbols, which are sent when no communication occurs, is not a convex combination of those induced by any other combination of input symbols (otherwise, the square-root law does not hold). We derive the exact covert capacity region and show that a simple point-topoint based scheme with treating interference as noise is optimal. In addition, we analyze the secret key length required for the reliable and covert communication with the desired rates, and present a channel condition where the secret key between each user pair is unnecessary.

We study the capacity scaling of the covert communication over a wireless ad hoc network where n mobile nodes want to communicate each other in a unit disk while keeping the presence of the communication secret from each of Θ(ns) non-colluding wardens (0 <; s <; 1). We modify the two-hop based scheme by Grossglauser and Tse (2002), which is proposed for a wireless ad hoc network without a covertness constraint, by introducing a preservation region around each warden in which the senders are not allowed to transmit. This scheme is shown to be optimal under an assumption that each node outside the preservation regions uses the same transmit power. Our results show that the node mobility greatly improves the aggregate throughput, compared to the case of fixed node location. In particular, the aggregate throughput scaling is shown to be linear in n when the number of channel uses that each warden uses to judge the presence of communication is not too large compared to n.

We consider the problem of covert communication over wireless adhoc networks in which (roughly) n legitimate nodes (LNs) and nκfor κ > 0 non-communicating warden nodes (WNs) are randomly distributed in a square of unit area. Each legitimate source wants to communicate with its intended destination node while ensuring that every WN is unable to detect the presence of the communication. In this scenario, we study the throughput scaling law. Due to the covert communication constraint, the transmit powers are necessarily limited. Under this condition, we introduce a preservation region around each WN. This regionsuitably modified by taking a detour around each preservation region. To avoid the concentration of detours resulting extra relaying burdens, we distribute the detours evenly over a wide region. In the proposed HC scheme, we control the symbol power and the scheduling of distributed multiple-input multiple-output transmission. We also present upper bounds on the throughput scaling under the assumption that every active LN consumes the same average transmit power over the time period in which the WNs observe the channel outputs. For 0 <; κ <; 1, these upper bounds match with the achievable throughput scalings.

We study the throughput scaling law of covert communication over wireless adhoc networks where (roughly) n legitimate nodes (LNs) and nκfor 0 <; κ <; 1 warden nodes (WNs) are randomly distributed in a unit area. Each legitimate source wants to communicate with its destination while ensuring that each WN is unable to detect the presence of communication. A preservation region, where the transmission of the LNs is not permitted, is introduced around each WN to increase the transmit power of the LNs outside the preservation regions. For achievability, multi-hop (MH), hierarchical cooperation (HC), and hybrid HC-MH schemes in the literature are utilized with some modifications. In the MH and the hybrid schemes, because the preservation regions may block the direct data paths, a detouring method that distributes the detours evenly over a wide region is proposed to avoid the concentration of relaying burdens. In the HC scheme, we properly control the symbol power and the MIMO transmission scheduling. We also present matching upper bounds on the throughput scaling under an assumption that every active LN consumes a same average transmit power over the time period that the WNs observe.

We consider the Gaussian wiretap channel with onebit analog-to-digital converters (ADCs) at both the legitimate receiver and the eavesdropper. In this channel, we show that a positive secrecy rate is always achievable whenever the noise power n12at the legitimate receiver is not the same as the noise power n22at the eavesdropper. A binary phase-shift keying (BPSK) and an asymmetric BPSK are shown to achieve a positive secrecy rate for the cases of n12and n1> n2, respectively. We partially justify the choice of these signalings by showing that the optimal input distribution that achieves Rs* := supPX:E[X2]≤PI(X; Y1) - I(X; Y2), where X is the channel input with power constraint of P, and Y1and Y2are the channel outputs at the legitimate receiver and the eavesdropper, respectively, should satisfy some symmetric and asymmetric properties for the cases of n12and n1> n2, respectively. Moreover, for n12and sufficiently large P, it is shown that a BPSK using power smaller than P achieves Rs*.

In smart metering systems, a rechargeable battery can be utilized to protect the privacy of a user from the utility provider by partially masking the load profile of the user. In this line of research on using rechargeable batteries for privacy protection, most existing works have studied only single-user systems using rechargeable batteries. In this letter, we consider a multi-user scenario where the power supplies of two or more users are combined before sending them to the utility provider. We study the effect of such a user cooperation on enhancing the user privacy by deriving upper and lower bounds on the minimum leakage rate. Our simulation results show that the information leakage of each user can be reduced by a factor of the total number of cooperative users.

We consider a covert communication scenario where a transmitter wishes to communicate simultaneously to two legitimate receivers while ensuring that the communication is not detected by an adversary, the warden. The legitimate receivers and the adversary observe the transmission from the transmitter via a three-user discrete or Gaussian memoryless broadcast channel. We focus on the case where the “no-input” symbol is not redundant, i.e., the output distribution at the warden induced by the no-input symbol is not a mixture of the output distributions induced by other input symbols, so that the covert communication is governed by the square root law, i.e., at most Θ(√n) bits can be transmitted over n channel uses. We show that for such a setting, a simple time-division strategy achieves the optimal throughputs for a non-trivial class of broadcast channels; this is not true for communicating over broadcast channels without the covert communication constraint. Our result implies that a code that uses two separate optimal point-to-point codes each designed for the constituent channels and each used for a fraction of the time is optimal in the sense that it achieves the best constants of the √n-scaling for the throughputs. Our proof strategy combines several elements in the network information theory literature, including concave envelope representations of the capacity regions of broadcast channels and El Gamal's outer bound for more capable broadcast channels.

We consider a covert communication scenario where a transmitter wishes to communicate simultaneously to two legitimate receivers while ensuring that the communication is not detected by an adversary, the warden. The legitimate receivers and the adversary observe the transmission from the transmitter via a three-user discrete or Gaussian memoryless broadcast channel. We focus on the case where the “no-input” symbol is not redundant, i.e., the output distribution at the warden induced by the no-input symbol is not a mixture of the output distributions induced by other input symbols, so that the covert communication is governed by the square root law, i.e., at most Θ(√n) bits can be transmitted over n channel uses. We show that for such a setting, a simple time-division strategy achieves the optimal throughputs for a class of broadcast channels. Our result implies that a code that uses two separate optimal point-to-point codes each designed for the constituent channels and each used for a fraction of the time is optimal in the sense that it achieves the best constants of the √n-scaling for the throughputs. Our proof strategy combines several elements in the network information theory literature, including concave envelope representations of the capacity regions of broadcast channels and El Gamal's outer bound for more capable broadcast channels.

We consider the problem of covert communication over a state-dependent channel, where the transmitter has causal or noncausal knowledge of the channel states. Here, covert means that a warden on the channel should observe similar statistics when the transmitter is sending a message and when it is not. When a sufficiently long secret key is shared between the transmitter and the receiver, we derive closed-form formulas for the maximum achievable covert communication rate (covert capacity) for discrete memoryless channels and, when the transmitter's channel-state information (CSI) is noncausal, for additive white Gaussian noise (AWGN) channels. For certain channel models, including the AWGN channel, we show that the covert capacity is positive with CSI at the transmitter, but is zero without CSI. We also derive lower bounds on the rate of the secret key that is needed for the transmitter and the receiver to achieve the covert capacity.

In this paper, we prove a unified achievability bound that generalizes and improves random coding bounds for any combination of source coding, channel coding, joint source-channel coding, and coding for computing problems assuming blockwise node operation. As a general network setup, we consider an acyclic discrete memoryless network, where the network demands and constraints are specified by a joint-typicality constraint on the whole channel input and output sequences. For achievability, a basic building block for node operation consists of simultaneous nonunique decoding, simultaneous compression, and symbol-by-symbol mapping. Our bound can be useful for deriving random coding bounds without error analysis, especially for large and complex networks. In particular, our bound can be used for unifying and generalizing many known relaying strategies. For example, a generalized decode-compress-amplify-and-forward bound is obtained as a simple corollary of our main theorem, and it is shown to strictly outperform the previously known relaying schemes. Furthermore, by exploiting the symmetry in our bound, we formally define and characterize three types of network duality based on channel input-output reversal and network flow reversal combined with packing-covering duality.

In this paper, we study a diamond-relay channel where the source is connected toMrelays through orthogonal links and the relays transmit to the destination over a wireless multiple-access channel in the presence of an eavesdropper. The eavesdropper not only observes the relay transmissions through another multiple-access channel but also observes a certain number of source-relay links. The legitimate terminals know neither the eavesdropper's channel state information nor the location of source-relay links revealed to the eavesdropper except the total number of such links. For this wiretapped diamond-relay channel, we establish the optimal secure d.o.f. In the achievability part, our proposed scheme uses the source-relay links to transmit a judiciously constructed combination of message symbols, artificial noise symbols, and fictitious message symbols associated with secure network coding. The relays use a combination of beamforming and interference alignment in their transmission scheme. For the converse part, we take a genie-aided approach assuming that the location of wiretapped links is known.

In this paper, a streaming transmission setup is considered, where an encoder observes a new message in the beginning of each block and a decoder sequentially decodes each message after a delay of T blocks. In this streaming setup, the fundamental interplay between the coding rate, the error probability, and the blocklength in the moderate deviations regime is studied. For output symmetric channels, the moderate deviations constant is shown to improve over the block coding or non-streaming setup by exactly a factor of T for a certain range of moderate deviations scalings. For the converse proof, a more powerful decoder, to which some extra information is fedforward is assumed. The error probability is bounded first for an auxiliary channel and this result is translated back to the original channel by using a newly developed change-of-measure lemma, where the speed of decay of the remainder term in the exponent is carefully characterized. For the achievability proof, a known coding technique that involves a joint encoding and decoding of fresh and past messages is applied with some manipulations in the error analysis.

We consider the problem of covert communication over a state-dependent channel, where the transmitter has non-causal knowledge of the channel states. Here, “covert” means that the probability that a warden on the channel can detect the communication must be small. In contrast with traditional models without noncausal channel-state information at the transmitter, we show that covert communication can be possible with positive rate. We derive closed-form formulas for the maximum achievable covert communication rate (“covert capacity”) in this setting for discrete memoryless channels as well as additive white Gaussian noise channels. We also derive lower bounds on the rate of the secret key that is needed for the transmitter and the receiver to achieve the covert capacity.

A rechargeable battery may alleviate the issue of privacy loss in a smart metering system by distorting a household's load profile. However, existing studies involve a single rechargeable battery, whereas in a network scenario, there could be multiple batteries connected together. In this letter, we study the extension where a user's electricity load is input into a network of two rechargeable batteries, connected in series, and operating individually. This battery network attempts to mask the user load from the utility provider. We focus on the case of independent identically distributed load profile and a system of ideal batteries with no conversion loss, and use normalized mutual information (leakage rate) as the privacy metric. We derive upper and lower bounds on the leakage rate in terms of (single-letter) mutual information expressions. On the achievability side, our information-theoretic upper bound captures the novel tension between minimizing the leakage across each individual battery and the effect of their joint interaction. For the lower bound, we show that a system with a single battery, whose storage capacity is the sum of the two individual batteries, can achieve a leakage rate at least as small as our proposed setup. Furthermore, we use simulations to compare achievable leakage of our proposed scheme with several baseline schemes. The achievable leakage rates obtained in this study could help us to elucidate the privacy performance of a network of batteries.

We consider streaming data transmission over a discrete memoryless channel. A new message is given to the encoder at the beginning of each block and the decoder decodes each message sequentially, after a delay of T blocks. In this streaming setup, we study the fundamental interplay between the rate and error probability in the central limit and moderate deviations regimes and show that: 1) in the moderate deviations regime, the moderate deviations constant improves over the block coding or non-streaming setup by a factor of T and 2) in the central limit regime, the second-order coding rate improves by a factor of approximately √T for a wide range of channel parameters. For both the regimes, we propose coding techniques that incorporate a joint encoding of fresh and previous messages. In particular, for the central limit regime, we propose a coding technique with truncated memory to ensure that a summation of constants, which arises as a result of applications of the central limit theorem, does not diverge in the error analysis. Furthermore, we explore interesting variants of the basic streaming setup in the moderate deviations regime. We first consider a scenario with an erasure option at the decoder, i.e., the decoder can output an erasure symbol instead of a message estimate, and show that both the exponents of the total error and the undetected error probabilities improve by factors of T. Next, by utilizing the erasure option, we show that the exponent of the total error probability can be improved to that of the undetected error probability (in the order sense) at the expense of a variable decoding delay.

In this paper, we consider the Gaussian diamond-wiretap channel that consists of an orthogonal broadcast channel from a source to two relays and a Gaussian fast-fading multiple access-wiretap channel from the two relays to a legitimate destination and an eavesdropper. For the multiple access part, we consider both the case with full channel state information (CSI) and the case with no eavesdropper's CSI, at the relays and the legitimate destination. For both the cases, we establish the exact secure degrees of freedom and generalize the results for multiple relays. For the converse part, we introduce a new technique of capturing the trade-off between the message rate and the amount of individual randomness injected at each relay. In the achievability part, we show (i) how to strike a balance between sending message symbols and common noise symbols from the source to the relays in the broadcast component and (ii) how to combine artificial noise-beamforming and noise-alignment techniques at the relays in the multiple access component.

In this paper, we take a unified approach for network information theory and prove a coding theorem, which can recover most of the achievability results in network information theory that are based on random coding. The final single-letter expression has a very simple form, which was made possible by treating sources, channels, states and side information in a unified way and by combining various constraints such as cost and distortion constraints as a single joint-typicality constraint. To demonstrate usefulness of our unified coding theorem, we show that a generalized decode-compress-amplify-and-forward bound can be obtained as a simple corollary of our theorem and show it strictly outperforms previously known coding schemes. Using our unified framework, we formally define and characterize three types of network duality based on channel input-output reversal and network flow reversal combined with packing-covering duality.

In this paper, we propose a noisy network coding integrated with partial decode-and-forward relaying for single-source multicast discrete memoryless networks (DMN's). Our coding scheme generalizes the partial-decode-compress-and-forward scheme (Theorem 7) by Cover and El Gamal. This is the first time the theorem is generalized for DMN's such that each relay performs both partial decode-and-forward and compress-and-forward simultaneously. Our coding scheme simultaneously generalizes both noisy network coding by Lim, Kim, El Gamal, and Chung and distributed decode-and-forward by Lim, Kim, and Kim. It is not trivial to combine the two schemes because of inherent incompatibility in their encoding and decoding strategies. We solve this problem by sending the same long message over multiple blocks at the source and at the same time by letting the source find the auxiliary covering indices that carry information about the message simultaneously over all blocks.

In this paper, we present nontrivial upper and lower bounds on the secrecy capacity of the degraded Gaussian diamond-wiretap channel and identify several ranges of channel parameters where these bounds coincide with useful intuitions. Furthermore, we investigate the effect of the presence of an eavesdropper on the capacity. We consider the following two scenarios regarding the availability of randomness: 1) a common randomness is available at the source and the two relays and 2) a randomness is available only at the source and there is no available randomness at the relays. We obtain the upper bound by taking into account the correlation between the two relay signals and the availability of randomness at each encoder. For the lower bound, we propose two types of coding schemes: 1) a decode-and-forward scheme where the relays cooperatively transmit the message and the fictitious message and 2) a partial DF scheme incorporated with multicoding in which each relay sends an independent partial message and the whole or partial fictitious message using dependent codewords.

We establish upper and lower bounds on the secrecy capacity of the degraded Gaussian diamond-wiretap channel, and identify several ranges of channel parameters where these bounds coincide with useful intuitions. Furthermore, we investigate the effect of the presence of an eavesdropper on the capacity. We consider the following two scenarios: 1) common randomness is available at the source and the two relays and 2) randomness is available only at the source, and there is no randomness at the relays. Our upper bounds are established by taking into account the correlation between the two relay signals and the available randomness at the encoders, which generalize the techniques recently developed for the case without secrecy constraint. For the lower bounds, we propose two types of coding schemes: 1) decode-and-forward schemes where the relays cooperatively transmit the message and the fictitious message and 2) partial decode-and-forward schemes incorporated with multicoding in which each relay sends an independent partial message and the whole or partial fictitious message using dependent codewords.

We establish an achievable rate region for discrete memoryless interference relay channels that consist of two source-destination pairs and one or more relays. We develop an achievable scheme combining Han-Kobayashi and noisy network coding. We apply our achievability to two cases. First, we characterize the capacity region of some classes of discrete memoryless interference relay channels. These classes naturally generalize the injective deterministic discrete memoryless interference channel by El Gamal and Costa and the discrete memoryless relay channel. Moreover, for the Gaussian interference relay channel with orthogonal receiver components, we show that our scheme achieves a better sum rate than that of noisy network coding.

In this paper, we characterize the capacity of a new class of discrete memoryless multicast networks having a tree topology. For achievability, a novel coding scheme is constructed where some relays employ a combination of decode-and-forward and compress-and-forward and the other relays perform a random binning such that codebook constructions and relay operations are independent for each node and do not depend on the network topology. For converse, a new technique of iteratively manipulating inequalities exploiting the tree topology is used. This class of multicast tree networks includes the class of diamond networks studied by Kang and Ulukus as a special case.

In this paper, message dissemination with node mobility is studied where each node in the network having mobility wants to send its message to all the other nodes. The channel capacity between two nodes is assumed to be large enough for exchanging all the messages they have when they get close enough. We show that what type of network graph enables each node to accumulate all messages in the network, and investigate the dissemination time T for all nodes to get all messages. For a general directed graph model, the upper and lower bounds on T are given as Θ(n2) and Θ(1), respectively. For some special cases, we present tighter bounds. For general undirected graph, T is upper bounded by Θ(n). For grid graph, T is an order of Θ(√n).

In this paper, we characterize the information-theoretic capacity scaling of wireless ad hoc networks with randomly distributed nodes. By using an exact channel model from Maxwell's equations, we successfully resolve the conflict in the literature between the linear capacity scaling by Özgür and the degrees of freedom limit given as the ratio of the network diameter and the wavelength by Franceschetti In dense networks where the network area is fixed, the capacity scaling is given as the minimum of and the degrees of freedom limit to within an arbitrarily small exponent. In extended networks where the network area is linear in , the capacity scaling is given as the minimum of and the degrees of freedom limit to within an arbitrarily small exponent. Hence, we recover the linear capacity scaling by Özgür if in dense networks and if in extended networks. Otherwise, the capacity scaling is given as the degrees of freedom limit characterized by Franceschetti For achievability, a modified hierarchical cooperation is proposed based on a lower bound on the capacity of multiple-input multiple-output channel between two node clusters using our channel model.

In this paper, we characterize the capacity of two new classes of relay channels, which we call more capable and less noisy relay channels. In these relay channels, the channel seen by the relay is stronger than that seen by the destination in a certain sense, which resembles the conditions for the more capable and less noisy broadcast channels. In more capable relay channels, decode-and-forward (DF) is shown to be optimal. The more capable relay channel includes as special cases several examples in the literature where DF is shown to be optimal. In less noisy relay channels, partial decode-and-forward (PDF) is shown to achieve the capacity. This is the third class of relay channels where PDF is shown to be optimal, where two previously known classes are the semideterministic relay channel and the relay channel with orthogonal components at the source. By using the definition of less noisy relay channel, we can easily construct many examples where DF is strictly suboptimal but PDF is capacity achieving.

In this paper, we characterize the capacity of a class of single-source single-destination discrete memoryless relay networks with an arbitrary number of nodes. In this class, the network is assumed to have a tree topology where the root node is the source, each parent node in the graph has at most one noisy child node and any number of noiseless child nodes, and the set of leaf nodes is the destination. A combination of decode-and-forward (DF) and compress-and-forward (CF) at noisy relay nodes is shown to be optimal. Our result is the first to show that the combination of DF and CF is capacity achieving for a non-trivial class of noisy networks with an arbitrary number of nodes.

In this paper, we study the capacity scaling of wireless ad hoc networks considering the effect of a finite wavelength, which gives a unified view on two seemingly contradictory results on the capacity scaling. Recently, it was shown that the order-optimal linear throughput scaling is achievable for some networks using hierarchical cooperation (HC) by Özgür et al., but later it was proved to violate the physical limit by Franceschetti et al. The cause of such a contradiction is the idealized channel model in the former that does not capture the channel correlation due to the finite wavelength. Taking into account such an effect of the finite wavelength, we construct a modified HC scheme and analyze its throughput scaling in terms of both the number of nodes and wavelength. Our result is consistent with the physical limit while recovering the linear throughput scaling asymptotically as the wavelength tends to zero.

In cellular networks, relays and/or mobiles can cooperate to improve the overall system performance. For example, once the transmission from a base station with multiple antennas is received by multiple nodes (relays and/or mobiles), they can exchange information to enhance the quality of intended signals while suppressing interference. Such virtual multiple- input multiple-output (MIMO) transmission is a key ingredient in hierarchical cooperation by Ozgiir et al., which was shown to improve the throughput scaling of ad hoc networks greatly. In this paper, we analyze the achievable rate of such a cooperative MIMO between a base station with multiple antennas and a node group. An antenna array with a fixed area has a limited number of degrees of freedom. We use a realistic channel model that can capture the effect of geometry of antenna arrays on the number of degrees of freedom. Our achievable rate is limited by the product of the aperture of the antenna array in the base station and the angular spread, which is consistent with some known results on the limit of the degrees of antenna arrays.

A hierarchical cooperative multiple-input multiple-output (MIMO) transmission can greatly improve the throughput scaling in wireless networks as shown in [1]. In this paper, we analyze the effect of channel correlation on the throughput scaling in wireless networks by focusing on an achievable rate of the cooperative MIMO transmission between two clusters of nodes as a function of the number of nodes in each cluster, the physical size of each cluster, and the distance between the two clusters. Channel correlation occurs naturally in a regime when the effect of the wavelength cannot be ignored. We use a realistic channel model that can model this channel correlation accurately. Although it is not critical, we assume more generally multiple antennas are allowed per node since this assumption becomes natural for our channel model. Our main results are in a sense consistent with the upper bounds in [2], [3] on the degrees of freedom in MIMO and in wireless networks.