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We consider the problem of communication over a three-user discrete memoryless interference channel (3-IC). The current known coding techniques for communicating over an arbitrary 3-IC are based on message splitting, superposition coding, and binning using independent and identically distributed (i.i.d.) random codebooks. In this paper, we propose a new ensemble of codes—partitioned coset codes (PCCs)—that possess an appropriate mix of empirical and algebraic closure properties. We develop coding techniques that exploit the algebraic closure property of PCC to enable interference alignment over general 3-IC. We analyze the performance of the proposed coding technique to derive an achievable rate region for the general discrete 3-IC. Additive and non-additive examples are identified for which the derived achievable rate region is the capacity, moreover, strictly larger than the current known largest achievable rate regions based on the i.i.d. random codebooks. [ABSTRACT FROM AUTHOR]

Wyner’s common information was originally defined for a pair of dependent discrete random variables. Its significance is largely reflected in, and also confined to, several existing interpretations in various source coding problems. This paper attempts to expand its practical significance by providing a new operational interpretation. In the context of the Gray–Wyner network, it is established that Wyner’s common information has a new lossy source coding interpretation. Specifically, it is established that, under suitable conditions, Wyner’s common information equals to the smallest common message rate when the total rate is arbitrarily close to the rate distortion function with joint decoding for the Gray–Wyner network. A surprising observation is that such equality holds independent of the values of distortion constraints as long as the distortions are within some distortion region. The new lossy source coding interpretation provides the first meaningful justification for defining Wyner’s common information for continuous random variables and the result can also be extended to that of multiple variables. Examples are given for characterizing the rate distortion region for the Gray–Wyner lossy source coding problem and for identifying conditions under which Wyner’s common information equals that of the smallest common rate. As a by-product, the explicit expression for the common information between a pair of Gaussian random variables is obtained. [ABSTRACT FROM AUTHOR]

In the wiretap model of secure communication, Alice is connected to Bob over a noisy channel that is eavesdropped by Eve. The goal is to provide (asymptotic) reliability and perfect secrecy assuming that the Eve has unlimited computational power. The model has attracted considerable attention in recent years because it provides a natural model for passive eavesdropping in wireless communication. We consider a wiretap model with active adversaries, and define adversarial wiretap (AWTP) channels using a (\rho r , \rho w) wiretap adversary who can read a fraction \rho r , and modify a fraction \rho w of a sent codeword. The code components that are read and/or modified can be chosen adaptively, and the subsets of read and modified components could be different. AWTP codes provide secrecy and reliability for communication over AWTP channels. We define the security and reliability of AWTP channels and use these definitions to evaluate the security and reliability of codes for these channels. This paper has two main contributions. First, we prove an upper bound on the rate of AWTP codes for (\rho r , \rho w) -AWTP channels. Second, we give an explicit construction of a perfectly secure AWTP code family with efficient decoding that achieves the bound and, hence, obtain the secrecy capacity of AWTP channels for large alphabets. AWTP model is a natural extension of Wyner’s wiretap models, and somewhat surprisingly, it is also closely related to a seemingly unrelated cryptographic primitive, secure message transmission (SMT). This relation results in a new (and the only known) bound on the transmission rate of 1-round $(\epsilon , \delta )$ -SMT protocols. We discuss our results, give their relations to other works, and propose directions for future work. [ABSTRACT FROM AUTHOR]

This paper studies the optimal points in the capacity region of Gaussian multiple access channels (GMACs) with constant fading, multiple antennas, and various power constraints. The points of interest maximize general rate objectives that arise in practical communication scenarios. Achieving these points constitutes the task of jointly optimizing the time-sharing parameters, the input covariance matrices, and the order of decoding used by the successive interference cancellation receiver. To approach this problem, Carathéodory’s theorem is invoked to represent time-sharing and decoding orders jointly as a finite-dimensional matrix variable. This variable enables us to use variational inequalities to extend results pertaining to problems with linear rate objectives to more general, potentially nonconvex, problems, and to obtain a necessary and sufficient condition for the optimality of the transmission parameters in a wide range of problems. Using the insights gained from this condition, we develop and analyze the convergence of an algorithm for solving, otherwise daunting, GMAC-based optimization problems. [ABSTRACT FROM PUBLISHER]

In this paper, the Gaussian many-to-one X channel (XC), which is a special case of general multiuser XC, is studied. In the Gaussian many-to-one XC, communication links exist between all transmitters and one of the receivers, along with a communication link between each transmitter and its corresponding receiver. As per the XC assumption, transmission of messages is allowed on all the links of the channel. This communication model is different from the corresponding many-to-one interference channel (IC). Transmission strategies, which involve using Gaussian codebooks and treating interference from a subset of transmitters as noise, are formulated for the above channel. Sum-rate is used as the criterion of optimality for evaluating the strategies. Initially, a $3 \times 3$ many-to-one XC is considered and three transmission strategies are analyzed. The first two strategies are shown to achieve sum-rate capacity under certain channel conditions. For the third strategy, a sum-rate outer bound is derived and the gap between the outer bound and the achieved rate is characterized. These results are later extended to the $K \times K$ case. Next, a region in which the many-to-one XC can be operated as a many-to-one IC without the loss of sum-rate is identified. Furthermore, in the above region, it is shown that using Gaussian codebooks and treating interference as noise achieve a rate point that is within $K/2 -1$ bits from the sum-rate capacity. Subsequently, some implications of the above results to the Gaussian many-to-one IC are discussed. Transmission strategies for the many-to-one IC are formulated, and channel conditions under which the strategies achieve sum-rate capacity are obtained. A region where the sum-rate capacity can be characterized to within $K/2-1$ bits is also identified. Finally, the regions where the derived channel conditions are satisfied for each strategy are illustrated for a $3 \times 3$ many-to-one XC and the corresponding many-to-one IC. [ABSTRACT FROM PUBLISHER]

The framework of network equivalence theory developed by Koetter et al. introduces a notion of channel emulation to construct noiseless networks as upper (respectively, lower) bounding models, which can be used to calculate the outer (respectively, inner) bounds for the capacity region of the original noisy network. Based on the network equivalence framework, this paper presents scalable upper and lower bounding models for wireless networks with potentially many nodes. A channel decoupling method is proposed to decompose wireless networks into decoupled multiple-access channels and broadcast channels. The upper bounding model, consisting of only point-to-point bit pipes, is constructed by first extending the one-shot upper bounding models developed by Calmon et al. and then integrating them with network equivalence tools. The lower bounding model, consisting of both point-to-point and point-to-points bit pipes, is constructed based on a two-step update of the lower bounding models to incorporate the broadcast nature of wireless transmission. The main advantages of the proposed methods are their simplicity and the fact that they can be extended easily to large networks with a complexity that grows linearly with the number of nodes. It is demonstrated that the resulting upper and lower bounds can approach the capacity in some setups. [ABSTRACT FROM PUBLISHER]

In this paper, a forward decoding procedure is developed for the compress-and-forward (CF) relaying scheme. This procedure uses a layered framework and is based on exploiting a feature of the $N$ -to-1 mapping inherent in the underlying Wyner–Ziv binning. It is shown that exploiting this mapping enables the relaxation of the constraint on the rate of the relay codewords representing the bin indices. For the cooperative multimessage network, the proposed procedure achieves the same rate region as the short-message noisy network coding (SNNC) scheme. However, this procedure is more advantageous for other networks including the two networks presented herein. The first network is a relay chain one with two destinations, whereas the second network is a partially cooperative multimessage one with three destinations. In both networks, side information is available to a subset of the decoding nodes, but not to the rest of the nodes, and in both cases, the network benefits from the relaxation of the rate of the CF bin indices. This relaxation results in rate regions larger than those achieved by the conventional CF and SNNC. [ABSTRACT FROM PUBLISHER]

Although interference alignment (IA) can theoretically achieve the optimal degrees of freedom (DoFs) in the $K$ -user Gaussian interference channel, its direct application comes at the prohibitive cost of precoding over exponentially many signaling dimensions. On the other hand, it is known that practical one-shot IA precoding (i.e., linear schemes without symbol expansion) provides a vanishing DoFs gain in large fully connected networks with generic channel coefficients. In our previous work, we introduced the concept of cellular IA for a network topology induced by hexagonal cells with sectors and nearest-neighbor interference. Assuming that neighboring sectors can exchange decoded messages (and not received signal samples) in the uplink, we showed that linear one-shot IA precoding over $M$ transmit/receive antennas can achieve the optimal $M/2$ DoFs per user. In this paper, we extend this framework to networks with omni-directional (non-sectorized) cells and consider a limited practical scenario where users have 2 antennas, and base-stations have 2, 3, or 4 antennas. We provide linear one-shot IA schemes for the $2\times 2$ , $2\times 3$ , and $2\times 4$ cases, and show the achievability of 3/4, 1, and 7/6 DoFs per user, respectively. DoFs converses for one-shot schemes require the solution of a discrete optimization problem over a number of variables that grows with the network size. We develop a new approach to transform such optimization problem into a tractable linear program with significantly fewer variables. This approach is used to show that 3/4 DoFs per user are indeed optimal for one-shot schemes over large (extended) cellular network with $2\times 2$ links. [ABSTRACT FROM AUTHOR]

In this paper, we extend the information theoretic framework that was developed in earlier works to multi-hop network settings. For a given network, we construct a novel deterministic model that quantifies the ability of the network in transmitting private and common messages across users. Based on this model, we formulate a linear optimization problem that explores the throughput of a multi-layer network, thereby offering the optimal strategy as to what kind of common messages should be generated in the network to maximize the throughput. With this deterministic model, we also investigate the role of feedback for multi-layer networks, from which we identify a variety of scenarios in which feedback can improve transmission efficiency. Our results provide fundamental guidelines as to how to coordinate cooperation between users to enable efficient information exchanges across them. [ABSTRACT FROM AUTHOR]

This paper investigates the design of codes for multiple-input multiple-output (MIMO) multiple access channel (MAC). If a joint maximum-likelihood decoding is to be performed at the receiver, then every MIMO-MAC code can be regarded as a single-user code, where the minimum determinant criterion proposed by Tarokh et al. is useful for designing such codes and for upper bounding the maximum pairwise error probability (PEP), whenever the codes are of finite rate and operate in finite signal-to-noise ratio range. Unlike the case of single-user codes where the minimum determinant can be lower bounded by a fixed constant as code-rate grows, it was proved by Lahtonen et al. that the minimum determinant of MIMO-MAC codes decays as a function of the rates. This decay phenomenon is further investigated in this paper, and upper bounds for the decays of minimum determinant corresponding to each error event are provided. Lower bounds for the optimal decay are established and are based on an explicit construction of codes using algebraic number theory and Diophantine approximation. For some error profiles, the constructed codes are shown to meet the aforementioned upper bounds, hence they are optimal finite-rate codes in terms of PEPs associated with such error events. An asymptotic diversity-multiplexing gain tradeoff (DMT) analysis of the proposed codes is also given. It is shown that these codes are DMT optimal when the values of multiplexing gains are small. [ABSTRACT FROM PUBLISHER]

Interference networks with no channel state information at the transmitter except for the knowledge of the connectivity graph have been recently studied under the topological interference management framework. In this paper, we consider a similar problem with topological knowledge but in a distributed broadcast channel setting, i.e., a network where transmitter cooperation is enabled. We show that the topological information can also be exploited in this case to strictly improve the degrees of freedom (DoF) as long as the network is not fully connected, which is a reasonable assumption in practice. Achievability schemes from graph theoretic and interference alignment perspectives are proposed. Together with outer bounds built upon generator sequence, the concept of compound channel settings, and the relation to index coding, we characterize the symmetric DoF for the so-called regular networks with constant number of interfering links, and identify the sufficient and/or necessary conditions for the arbitrary network topologies to achieve a certain amount of symmetric DoF. [ABSTRACT FROM PUBLISHER]

This paper investigates the secrecy capacity of the wiretap broadcast channel (WBC) with an external eavesdropper where a source wishes to communicate two private messages over a broadcast channel (BC) while keeping them secret from the eavesdropper. We derive a nontrivial outer bound on the secrecy capacity region of this channel which, in absence of security constraints, reduces to the best known outer bound to the capacity of the standard BC. An inner bound is also derived, which follows the behavior of both the best known inner bound for the BC and the wiretap channel. These bounds are shown to be tight for the deterministic BC with a general eavesdropper, the semideterministic BC with a more noisy eavesdropper, and the wiretap BC where users exhibit a less noisiness order between them. Finally, by rewriting our outer bound to encompass the characteristics of parallel channels, we also derive the secrecy capacity region of the product of two inversely less noisy BCs with a more noisy eavesdropper. We illustrate our results by studying the impact of security constraints on the capacity of the WBC with binary erasure and binary symmetric components. [ABSTRACT FROM PUBLISHER]

Two independent data streams are to be transmitted over a noisy discrete memoryless channel with noiseless (ideal) feedback. Errors are tolerated only in the second stream, provided that they occur with vanishing probability. The rate of the error-free stream cannot, of course, exceed the channel’s zero-error feedback capacity, and nor can the sum of the streams’ rates exceed the channel’s Shannon capacity. Using a suitable coding scheme, these necessary conditions are shown to characterize all the achievable rate pairs. Planning for the worst channel behavior—as is needed to achieve zero-error communication—and planning for the typical channel behavior—as is needed to communicate near the Shannon limit—are thus not incompatible. It is further shown that feedback may be beneficial for the multiplexing problem even on channels on which it does not increase the zero-error capacity. [ABSTRACT FROM AUTHOR]

We study exponential-server timing channels, in which the transmitter encodes a message using a sequence of packet inter-arrival times and the receiver observes the corresponding inter-departure times from an exponential-server queue. We show that if the service rate of one such queue is faster than that of another, then the latter channel is stochastically degraded with respect to the former. This combined with Burke’s theorem implies that the slower queue is more entropy increasing than the first. These facts put together provide a converse for the secrecy capacity of the wiretapped version of the channel, matching an earlier achievability result in the literature. [ABSTRACT FROM AUTHOR]

Using an algebraic approach based on the theory of Coxeter groups, we design, and describe the performance of, a class of line codes derived from permutation modulation, useful for parallel transmission of $b$ bits over $b+1$ wires, and admitting especially simple encoding and decoding algorithms. With these codes, resistance to common-mode noise is obtained by using codewords whose components sum to zero, simultaneous switching output noise is reduced by using constant-energy signals, and the effects of intersymbol interference are reduced by having decisions based on only two values at the input of the final slicers. Codebook design is based on the theory of Group Codes for the Gaussian Channel, as specialized to Coxeter matrix groups generated by reflections in orthogonal hyperplanes. A number of designs are exhibited, some of them being novel or improving on previously obtained codes. [ABSTRACT FROM AUTHOR]

Approximate capacity regions are established for a class of interfering multiple access channels consisting of two multiple-access channels (MACs), each with an arbitrary number of transmitters, with one transmitter in each MAC causing interference to the receiver of the other MAC, a channel we refer to henceforth as the MAC-IC-MAC. For the discrete memory-less (DM) MAC-IC-MAC, two inner bounds are obtained that are generalizations of prior inner bounds for the two-user DM interference channel (IC) due to Chong et al. For the semi-deterministic MAC-IC-MAC, it is shown that single-user coding at the non-interfering transmitters and superposition coding at the interfering transmitter of each MAC achieves a rate region that is within a quantifiable gap of the capacity region, thereby extending such a result for the two-user semi-deterministic IC by Telatar and Tse. For the Gaussian MAC-IC-MAC, an approximate capacity region that is within a constant gap of the capacity region is obtained, generalizing such a result for the two-user Gaussian IC by Etkin et al. On contrary to the aforementioned approximate capacity results for the two-user IC, whose achievability requires the union of all admissible input distributions, our gap results on the semi-deterministic and the Gaussian MAC-IC-MAC are achievable by only a subset and one of all admissible coding distributions, respectively. The symmetric generalized degrees of freedom (GDoFs) of the symmetric Gaussian MAC-IC-MAC with more than one user per cell, which is a function of the interference strength (the ratio of INR to SNR at high SNR, both expressed in dB) and the numbers of users in each cell, are V-shaped with flat shoulders. An analysis based on signal-level partitions shows that the non-interfering transmitters utilize the signal-level partitions at the receiver where they are intended that cannot be accessed by the interfering transmitters (due to the restriction of superposition coding), thereby improving the sum symmetric GDoF of up to one degree of freedom per cell under a range of SINR exponent levels, which in turn becomes wider as the number of transmitters in each cell increases. Consequently, time-sharing between interfering and non-interfering transmitters is GDoF-suboptimal in general, as is time-sharing between the two embedded MAC-Z-MACs. [ABSTRACT FROM AUTHOR]

In many wireless networks, link strengths are affected by many topological factors, such as different distances, shadowing, and intercell interference, thus resulting in some links being generally stronger than other links. From an information theoretic point of view, accounting for such topological aspects is still a novel approach, that has been recently fueled by strong indications that such aspects can crucially affect transceiver and feedback design, as well as the overall performance. This paper here takes a step in exploring this interplay between topology, feedback, and performance. This is done for the two user broadcast channel with random fading, in the presence of a simple two-state topological setting of statistically strong versus weaker links, and in the presence of a practical ternary feedback setting of alternating channel state information at the transmitter [alternating channel state information at the transmitter (CSIT)] where for each channel realization, this CSIT can be perfect, delayed, or not available. In this setting, the work derives generalized degrees-of-freedom bounds and exact expressions, that capture performance as a function of feedback statistics and topology statistics. The results are based on novel topological signal management schemes that account for topology in order to fully utilize feedback. This is achieved for different classes of feedback mechanisms of practical importance, from which we identify specific feedback mechanisms that are best suited for different topologies. This approach offers further insight on how to split the effort—of channel learning and feeding back CSIT—for the strong versus for the weaker link. Further intuition is provided on the possible gains from topological spatio-temporal diversity, where topology changes in time and across users [ABSTRACT FROM PUBLISHER]

This paper shows that the Maddah-Ali–Tse (MAT) scheme, which achieves the symmetric capacity of two example broadcast channels with strictly causal state information at the transmitter, is a simple special case of the Shayevitz–Wigger (SW) scheme for the broadcast channel with generalized feedback, which involves block Markov coding, Gray–Wyner compression, superposition coding, and Marton coding. Focusing on the class of symmetric broadcast channels with state, we derive an expression for the maximum achievable symmetric rate using the SW scheme. We show that the MAT results for the two-receiver case can be recovered by evaluating this expression for the special case in which superposition coding and Marton coding are not used. We then introduce a new broadcast channel example that shares many features of the MAT examples. We show that another special case of our maximum symmetric rate expression in which superposition coding is also used attains a higher symmetric rate than the MAT scheme. The symmetric capacity of this new example is not known, however. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the fluctuation of mutual information statistics of a multiple input multiple output channel communication systems without assuming that the entries of the channel matrix have zero pseudovariance. To this end, we also establish a central limit theorem of the linear spectral statistics for sample covariance matrices under general moment conditions by removing the restrictions imposed on the second moment and fourth moment on the matrix entries in Bai and Silverstein (2004). [ABSTRACT FROM AUTHOR]

We study a number of two-user interference networks with multiple-antenna transmitters/receivers (MIMO), transmitter side information in the form of linear combinations (over an appropriate finite-field) of the information messages, and two-hop relaying. We start with a cognitive interference channel (CIC) where one of the transmitters (noncognitive) has knowledge of a rank-1 linear combination of the two information messages, while the other transmitter (cognitive) has access to a rank-2 linear combination of the same messages. This is referred to as the network-coded CIC, since such linear combination may be the consequence of some random linear network coding scheme implemented in the backbone wired network. For such channel we develop an achievable region based on a few novel concepts: precoded compute-and-forward (PCoF) with channel integer alignment (CIA), combined with standard dirty-paper coding. We also develop a capacity region outer bound and find the symmetric generalized degrees of freedom (GDoF) region of the network-coded CIC. Through the GDoF characterization, we show that knowing mixed data (linear combinations of the information messages) provides a unbounded spectral efficiency gain over the classical CIC counterpart, if the ratio (in decibel) of signal-to-noise (SNR) to interference-to-noise is larger than certain threshold. Then, we consider a Gaussian relay network having the two-user MIMO IC as the main building block. We use PCoF with CIA to convert the MIMO IC into a deterministic finite-field IC. Then, we use a linear precoding scheme over the finite-field to eliminate interference in the finite-field domain. Using this unified approach, we derive the symmetric sum rate of the two-user MIMO IC with coordination, cognition, and two-hops. We also provide finite-SNR results (not just DoF) which show that the proposed coding schemes are competitive against state-of-the-art interference avoidance scheme based on orthogonal access, for standard randomly generated Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

This paper presents polar coding schemes for the two-user discrete memoryless broadcast channel (DM-BC) which achieve Marton’s region with both common and private messages. This is the best achievable rate region known to date, and it is tight for all classes of two-user DM-BCs whose capacity regions are known. To accomplish this task, we first construct polar codes for both the superposition as well as binning strategy. By combining these two schemes, we obtain Marton’s region with private messages only. Finally, we show how to handle the case of common information. The proposed coding schemes possess the usual advantages of polar codes, i.e., they have low encoding and decoding complexity and a superpolynomial decay rate of the error probability. We follow the lead of Goela, Abbe, and Gastpar, who recently introduced polar codes emulating the superposition and binning schemes. To align the polar indices, for both schemes, their solution involves some degradedness constraints that are assumed to hold between the auxiliary random variables and channel outputs. To remove these constraints, we consider the transmission of $k$ blocks and employ a chaining construction that guarantees the proper alignment of the polarized indices. The techniques described in this paper are quite general, and they can be adopted to many other multiterminal scenarios whenever there polar indices need to be aligned. [ABSTRACT FROM AUTHOR]

An open-loop single-user multiple-input multiple-output (MIMO) communication scheme is considered where a transmitter, equipped with multiple antennas, encodes the data into independent streams all taken from the same linear code. The coded streams are then linearly precoded using the encoding matrix of a perfect linear dispersion space-time code. At the receiver side, integer-forcing equalization is applied, followed by standard single-stream decoding. It is shown that this communication architecture achieves the capacity of any Gaussian MIMO channel up to a gap that depends only on the number of transmit antennas. [ABSTRACT FROM PUBLISHER]

Vector space interference alignment (IA) is known to achieve high degrees of freedom (DoFs) with infinite-independent channel extensions, but its performance is largely unknown for a finite number of possibly dependent channel extensions. In this paper, we consider a K -user M_{t} \times M_{r} MIMO interference channel (IC) with an arbitrary number of channel extensions T and arbitrary channel diversity order L (i.e., each channel matrix is a generic linear combination of L fixed basis matrices). We study the maximum DoF achievable via vector space IA in the single beam case (i.e., each user sends one data stream). We prove that the total number of users K , where N = \min \MtT, MrT \ . An immediate consequence of this upper bound is that for a Single-Input Single-Output (SISO) IC the DoF in the single beam case is no more than \min \big \{\sqrt { {5}/{4}K}, L + {1}/{4}T\big \} . When the channel extensions are independent, i.e., L achieves the maximum M_{r} M_{t} T , we show that this maximum DoF lies in [M_{r} + Mt – 1, Mr + Mt] regardless of $T$ . Unlike the well-studied constant MIMO IC case, the main difficulty is how to deal with a hybrid system of equation (zero-forcing condition) and inequalities (full rank condition). Our approach combines algebraic tools that deal with equations with an induction analysis that indirectly considers the inequalities. [ABSTRACT FROM PUBLISHER]

We study memoryless channels with synchronization errors as defined by a stochastic channel matrix allowing for symbol drop-outs or symbol insertions with particular emphasis on the binary and non-binary deletion channels. We offer a different look at these channels by considering equivalent models by fragmenting the input sequence where different subsequences travel through different channels. The resulting output symbols are combined appropriately to come up with an equivalent input–output representation of the original channel which allows for derivation of new upper bounds on the channel capacity. We consider both random and deterministic types of fragmentation processes applied to binary and nonbinary deletion channels. With two specific applications of this idea, a random fragmentation applied to a binary deletion channel and a deterministic fragmentation process applied to a nonbinary deletion channel, we prove certain inequality relations among the capacities of the original channels and those of the introduced subchannels. The resulting inequalities prove useful in deriving tighter capacity upper bounds for: 1) independent identically distributed (i.i.d.) deletion channels when the deletion probability exceeds 0.65 and 2) nonbinary deletion channels. Some extensions of these results, for instance, to the case of deletion/substitution channels are also explored. [ABSTRACT FROM PUBLISHER]

This paper addresses the following question regarding Gaussian networks: Is there an alternative to decoding interference or treating interference as Gaussian noise? To state our result, we study a decentralized network of one primary user (PU) and one secondary user (SU) modeled by a two-user Gaussian interference channel. In one scenario, the primary transmitter is constellation-based and PUs codebook is constructed over its modulation signal set. Assuming SU is aware of the constellation points of PU, the interference plus noise at the secondary receiver is modeled by a mixed Gaussian process. We show that SU can achieve larger rates by matching its decoder to the actual interference plus noise compared with the case where the secondary receiver performs nearest neighbor decoding (NND). In another scenario, we assume that PU utilizes a predetermined point-to-point code. We ask if SU can utilize its knowledge about PUs codebook without decoding PUs codewords. The proposed strategy assumes each transmitted codeword of SU overlaps with infinitely many transmitted codewords of PU, referred to as the unequal codeword-length (UCL) strategy. The secondary receiver views PU as a virtual user that is constellation-based and its modulation signal set is the codebook of the actual PU. UCL is compared with other strategies, namely, interference cancellation (IC), joint decoding, and NND. It is shown that UCL can outperform both IC and NND simultaneously. [ABSTRACT FROM PUBLISHER]

An erasure broadcast network is considered with two disjoint sets of receivers: a set of weak receivers with all-equal erasure probabilities and equal cache sizes and a set of strong receivers with all-equal erasure probabilities and no cache memories. Lower and upper bounds are presented on the capacity-memory tradeoff of this network (the largest rate at which messages can be reliably communicated for given cache sizes). The lower bound is achieved by means of a joint cache-channel coding scheme and significantly improves over traditional schemes based on the separate cache-channel coding. In particular, it is shown that the joint cache-channel coding offers new global caching gains that scale with the number of strong receivers in the network. The upper bound uses bounding techniques from degraded broadcast channels and introduces an averaging argument to capture the fact that the contents of the cache memories are designed before knowing users’ demands. The derived upper bound is valid for all stochastically degraded broadcast channels. The lower and upper bounds match for a single weak receiver (and any number of strong receivers) when the cache size does not exceed a certain threshold. Improved bounds are presented for the special case of a single weak and a single strong receiver with two files and the bounds are shown to match over a large range of cache sizes. [ABSTRACT FROM AUTHOR]

The minrank of a directed graph $G$ is the minimum rank of a matrix $M$ that can be obtained from the adjacency matrix of $G$ by switching some ones to zeros (i.e., deleting edges) and then setting all diagonal entries to one. This quantity is closely related to the fundamental information-theoretic problems of (linear) index coding (Bar-Yossef et al.), network coding (Effros et al.), and distributed storage (Mazumdar, ISIT, 2014). We prove tight bounds on the minrank of directed Erdős–Rényi random graphs $G(n,p)$ for all regimes of $p\in [{0,1}]$. In particular, for any constant $p$ , we show that $\mathsf {minrk}(G) = \Theta (n/\log n)$ with high probability, where $G$ is chosen from $G(n,p)$. This bound gives a near quadratic improvement over the previous best lower bound of $\Omega (\sqrt {n})$ (Haviv and Langberg), and partially settles an open problem raised by Lubetzky and Stav. Our lower bound matches the well-known upper bound obtained by the “clique covering” solution and settles the linear index coding problem for random knowledge graphs. [ABSTRACT FROM AUTHOR]

The minimum energy, and, more generally, the minimum cost, to transmit 1 bit of information was recently derived for bursty communication when the information is available infrequently at random times at the transmitter. This result assumes that the receiver is always in the listening mode and samples all channel outputs until it makes a decision. Since sampling is in practice one of the receiver’s most energy consuming functions, a natural question is to evaluate capacity per unit cost when the receiver is sampling constrained. This paper investigates such a setting where the receiver can sample only a given fraction $ \rho \in (0, 1]$ of the channel outputs. It is shown that regardless of $ \rho > 0$ , the asynchronous capacity per unit cost is the same as under full sampling, i.e., when $ \rho = 1$ . Moreover, a sparse output sampling does not even impact decoding delay—the elapsed time between when information is available and when it is decoded. Hence, surprisingly, it suffices to sample an arbitrarily small fraction of the channel outputs and yet achieve the same (asymptotic) performance as under full output sampling. [ABSTRACT FROM AUTHOR]

Function computation over Gaussian networks with orthogonal components is studied for arbitrarily correlated discrete memoryless sources. Two classes of functions are considered: 1) the arithmetic sum function and 2) the type function. The arithmetic sum function in this paper is defined as a set of multiple weighted arithmetic sums, which includes averaging of the sources and estimating each of the sources as special cases. The type or frequency histogram function counts the number of occurrences of each argument, which yields various fundamental statistics, such as mean, variance, maximum, minimum, median, and so on. The proposed computation coding first abstracts Gaussian networks into the corresponding modulo sum multiple-access channels via nested lattice codes and linear network coding and then computes the desired function using linear Slepian–Wolf source coding. For orthogonal Gaussian networks (with no broadcast and multiple-access components), the computation capacity is characterized for a class of networks. For Gaussian networks with multiple-access components (but no broadcast), an approximate computation capacity is characterized for a class of networks. [ABSTRACT FROM AUTHOR]

The interference channel with common information (IC-CI) consists of two transmit–receive pairs that communicate over a common noisy medium. Each transmitter has an individual message for its paired receiver, and additionally, both transmitters have a common message to deliver to both receivers. In this paper, through explicit inner and outer bounds on the capacity region, we establish the capacity region of the Gaussian IC-CI to within a bounded gap of one bit, independently of the values of all channel parameters. Using this constant-gap characterization, the generalized degrees of freedom (GDoF) region is determined. It is shown that the introduction of the common message leads to an increase in the GDoF over that achievable over the Gaussian interference channel without a common message, and hence, to an unbounded improvement in the achievable rate. A surprising feature of the capacity-within-one-bit result is that most of the available benefit (i.e., to within one bit of capacity) due to the common message is achieved through a simple and explicit coding scheme that involves independent signaling at the two transmitters so that, in effect, this scheme forgoes the opportunity for transmitter cooperation that is inherently available due to shared knowledge of the common message at both transmitters. [ABSTRACT FROM AUTHOR]

We show how to efficiently simulate the sending of a single message \(M\) to a receiver who has partial information about the message, so that the expected number of bits communicated in the simulation is close to the amount of additional information that the message reveals to the receiver. This is a generalization and strengthening of the Slepian–Wolf theorem, which shows how to carry out such a simulation with low amortized communication in the case that \(M\) is a deterministic function of \(X\) . A caveat is that our simulation is interactive. As a consequence, we prove that the internal information cost (namely the information revealed to the parties) involved in computing any relation or function using a two party interactive protocol is exactly equal to the amortized communication complexity of computing independent copies of the same relation or function. We also show that the only way to prove a strong direct sum theorem for randomized communication complexity is by solving a particular variant of the pointer jumping problem that we define. This paper implies that a strong direct sum theorem for communication complexity holds if and only if efficient compression of communication protocols is possible. In particular, together with our result, a recent result of Ganor, Kol, and Raz implies that the strongest version of direct sum for randomized communication complexity is false. [ABSTRACT FROM AUTHOR]

We study a two-transmitter two-receiver network where Receiver 1 can only hear the transmitted signal of Transmitter 1. Transmitter 1 has two messages, one of which is intended for Receiver 1 while both are intended for Receiver 2. Transmitter 2 has one message which is intended for Receiver 2. We call this channel model the Z channel with degraded message sets. For networks with the element of distributed encoding, it has been shown that when the multiple access link between the two encoders and the decoder satisfies the conditions proposed by Liu and Goldsmith, capacity results can be obtained for a variety of problems. In this paper, we generalize these conditions and show that for a larger class of multiple access links, the capacity region of the Z channel with degraded message sets can be characterized despite the presence of distributed encoding. [ABSTRACT FROM AUTHOR]

Network coding encourages information coding across a communication network. While the necessity, benefit and complexity of network coding are sensitive to the underlying graph structure of a network, existing theory on network coding often treats the network topology as a black box, focusing on algebraic or information theoretic aspects of the problem. This paper aims at an in-depth examination of the relation between algebraic coding and network topologies. We mathematically establish a series of results along the direction of: if network coding is necessary/beneficial, or if a particular finite field is required for coding, then the network must have a corresponding hidden structure embedded in its underlying topology, and such embedding is computationally efficient to verify. Specifically, we first formulate a meta-conjecture, the NC-minor conjecture, that articulates such a connection between graph theory and network coding, in the language of graph minors. We next prove that the NC-minor conjecture for multicasting two information flows is almost equivalent to the Hadwiger conjecture, which connects graph minors with graph coloring. Such equivalence implies the existence of \(K_{4}\) , \(K_{5}\) , \(K_{6}\) , and \(K_{O(q/\log {q})}\) minors, for networks that require \(\mathbb {F}_{3}\) , \(\mathbb {F}_{4}\) , \(\mathbb {F}_{5}\) , and \(\mathbb {F}_{q}\) to multicast two flows, respectively. We finally prove that, for the general case of multicasting arbitrary number of flows, network coding can make a difference from routing only if the network contains a \(K_{4}\) minor, and this minor containment result is tight. Practical implications of the above results are discussed. [ABSTRACT FROM AUTHOR]

We derive universal classical-quantum superposition coding and universal classical-quantum multiple access channel coding by using generalized packing lemmas for the type method. Using our classical-quantum universal superposition code, we establish the capacity region of a classical-quantum compound broadcast channel with degraded message sets. Our universal classical-quantum multiple access channel codes have two types of codes. One is a code with joint decoding and the other is a code with separate decoding. It is not so easy to construct a former code that universally achieves general points of the capacity region beyond corner points. First, we construct the latter code that universally achieves general points of the capacity region. Then, converting the latter code to the former coder, we construct the above desired code with the former type. [ABSTRACT FROM AUTHOR]

In this paper, we develop the machinery of real interference alignment. This machinery is extremely powerful in achieving the sum degrees of freedom (DoF) of single antenna systems. The scheme of real interference alignment is based on designing single-layer and multilayer constellations used for modulating information messages at the transmitters. We show that constellations can be aligned in a similar fashion as that of vectors in multiple antenna systems and space can be broken up into fractional dimensions. The performance analysis of the signaling scheme makes use of a recent result in the field of Diophantine approximation, which states that the convergence part of the Khintchine–Groshev theorem holds for points on nondegenerate manifolds. Using real interference alignment, we obtain the sum DoF of two model channels, namely the Gaussian interference channel (IC) and the \(X\) channel. It is proved that the sum DoF of the \(K\) -user IC is \(({K}/{2})\) for almost all channel parameters. We also prove that the sum DoF of the \(X\) -channel with \(K\) transmitters and \(M\) receivers is \(({KM}/{K+M-1})\) for almost all channel parameters. [ABSTRACT FROM PUBLISHER]

This paper defines the squashed entanglement of a quantum channel as the maximum squashed entanglement that can be registered by a sender and receiver at the input and output of a quantum channel, respectively. A new subadditivity inequality for the original squashed entanglement measure of Christandl and Winter leads to the conclusion that the squashed entanglement of a quantum channel is an additive function of a tensor product of any two quantum channels. More importantly, this new subadditivity inequality, along with prior results of Christandl and Winter, establishes the squashed entanglement of a quantum channel as an upper bound on the quantum communication capacity of any channel assisted by unlimited forward and backward classical communication. A similar proof establishes this quantity as an upper bound on the private capacity of a quantum channel assisted by unlimited forward and backward public classical communication. This latter result is relevant as a limitation on rates achievable in quantum key distribution. As an important application, we determine that these capacities can never exceed \(\log ( ( 1+\eta ) / ( 1-\eta ) ) \) for a pure-loss bosonic channel for which a fraction \(\eta \) of the input photons make it to the output on average. The best known lower bound on these capacities is equal to \(\log ( 1 / ( 1-\eta ) )\) . Thus, in the high-loss regime for which \(\eta \ll 1\) , this new upper bound demonstrates that the protocols corresponding to the above lower bound are nearly optimal. [ABSTRACT FROM PUBLISHER]

In this paper, the discrete memoryless arbitrarily varying broadcast channel (AVBC) with receiver side information is studied and its random code and deterministic code capacity regions are derived for the average error criterion. In addition, it is analyzed for deterministic list codes and it is shown that the corresponding list capacity region displays a behavior, which is similar to Ahlswede’s famous dichotomy result for the single-user arbitrarily varying channel: it either equals the random code capacity region or otherwise has an empty interior. This is characterized in terms of list sizes at the receivers and an appropriate concept of symmetrizability for the AVBC with receiver side information. The scenario studied here is motivated by the broadcast phase of bidirectional relaying, where a half-duplex relay node establishes a bidirectional communication between two other nodes using a decode-and-forward protocol. The relay decodes the messages both nodes have sent in the initial multiple access phase and broadcasts a re-encoded composition of them in the succeeding broadcast phase. Then, the broadcast phase corresponds to the AVBC with receiver side information, which differs from the classical broadcast channel, since both receivers can exploit their own messages from the previous phase as side information for decoding. [ABSTRACT FROM PUBLISHER]

We consider a broadcast channel with three receivers and three-degraded message sets, i.e., the transmitter has a common message intended for all three receivers, a message intended for receivers 2 and 3, and a private message intended only for receiver 3. The messages are transmitted over a family of parallel degraded broadcast channels. In the most general case, the broadcast channel consists of the product of six parallel degraded broadcast channels, each with a different order of degradedness. We first consider an achievable rate region of Nair and El Gamal, by appropriately choosing independent input random variables and auxiliary random variables for each subchannel. We then show that the achievable rate region attains the capacity region for two different classes of such broadcast channels, one consisting of the product of five parallel degraded broadcast channels and another consisting of the product of three parallel degraded broadcast channels. To accomplish this, we make use of an information-theoretic inequality that may be proven using the Csiszár-sum identity. Next, we extend the result to the Gaussian case. We consider the aligned Gaussian MIMO broadcast channel consisting of the product of six parallel degraded Gaussian broadcast channels, where the Gaussian noise vectors for each of the users in each of the subchannels follow a degradedness order, i.e., the noise covariance matrices may be ordered in a positive semi-definite sense. We show that the Nair–El Gamal achievable rate region considered in this paper is maximized by Gaussian inputs. To prove that Gaussian inputs are optimal, we prove an extremal entropy inequality employing a new method recently introduced by Geng and Nair to prove the capacity region of the two-user Gaussian MIMO broadcast channel with common and private messages. [ABSTRACT FROM AUTHOR]

Discrete memoryless multicast network (DM-MN) is considered in this paper. We analyze the lower bounds of noisy network coding (NNC) and distributed decode-forward (DDF) for DM-MN, and show that both NNC and DDF ignore the channel output observed at the transmitter. Motivated by this observation, new coding schemes are proposed to improve NNC and DDF by exploiting the transmitter’s observation and applying hybrid relaying strategies. We first study a special case when the transmitter’s observation is rate-limited feedback signals, and propose a scheme that strictly improves NNC when feedback rates are sufficiently large. For the relay channel with perfect relay-transmitter feedback, our achievable rate reduces to Gabbai and Bross’s rate, which is strictly larger than NNC, DDF, and all known lower bounds on the achievable rates proposed for the setup without feedback. In our scheme, both relays and receivers compress their received signals like NNC, and the relays decode independent “common” and “private” parts of the source message. The generated compression indices are sent to the transmitter through feedback, from which the transmitter reconstructs the receivers’ and relays’ inputs and can thus cooperate with the receivers and relays. We then extend our idea to DM-MN without feedback. For this case, although the transmitter observes channel output, both NNC and DDF simply ignore it, while our new scheme has the transmitter utilize its channel output to decode a set of relays’ and receivers’ compression indices, which achieves some cooperation levels between the transmitter and the receivers and relays. An enhanced relay channel is introduced to show that our scheme strictly outperforms NNC and DDF. [ABSTRACT FROM AUTHOR]

Linear network coding over finite fields is a well-studied problem. We consider the more general setting of linear coding for directed acyclic networks with finite commutative ring alphabets. Our results imply that for scalar linear network coding over commutative rings, fields can always be used when the alphabet size is flexible, but other rings may be needed when the alphabet size is fixed. We prove that if a network has a scalar linear solution over some finite commutative ring, then the (unique) smallest such commutative ring is a field. We also show that fixed-size commutative rings are quasi-ordered, such that all the scalar linearly solvable networks over any given ring are also scalar linearly solvable over any higher-ordered ring. We study commutative rings that are maximal with respect to this quasi-order, as they may be considered the best commutative rings of a given size. We prove that a commutative ring is maximal if and only if some network is scalar linearly solvable over the ring, but not over any other commutative ring of the same size. Furthermore, we show that maximal commutative rings are direct products of certain fields specified by the integer partitions of the prime factor multiplicities of the ring’s size. Finally, we prove that there is a unique maximal commutative ring of size $m$ if and only if each prime factor of m$ has multiplicity in {1, 2, 3, 4, 6}. As consequences, 1) every finite field is such a maximal ring and 2) for each prime p$ , some network is scalar linearly solvable over a commutative ring of size but not over the field of the same size if and only if k \not \in \{1,2,3,4,6\} . [ABSTRACT FROM PUBLISHER]

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

We consider the problem of non-coherent interference alignment, in which the goal is to align the signals of multiple interfering transmitters at a single receiver where the transmitters are not aware of the channel state information. We cast this problem as a problem of determining rank loss conditions for a column concatenation of full-rank matrices, such that each row of the composing matrices is scaled by a random coefficient. We determine necessary and sufficient conditions for the design of each matrix, such that the random ensemble will almost surely lose rank by a certain amount. The result is proved by converting the problem to determining rank loss conditions for the union of some specific matroids, and then using tools from matroid and graph theories to derive the necessary and sufficient conditions. As an application, we discuss how this result can be applied to the problem of topological interference management, and characterize the linear symmetric degrees of freedom for a class of network topologies. [ABSTRACT FROM PUBLISHER]

Suppose that we have r sensors and each one intends to send a function {g}_{i} (e.g., a signal or an image) to a receiver common to all r sensors. During transmission, each gi gets convolved with a function {f}i . The receiver records the function y , given by the sum of all these convolved signals. When and under which conditions is it possible to recover the individual signals gi and the blurring functions fi from just one received signal y ? This challenging problem, which intertwines blind deconvolution with blind demixing, appears in a variety of applications, such as audio processing, image processing, neuroscience, spectroscopy, and astronomy. It is also expected to play a central role in connection with the future Internet-of-Things. We will prove that under reasonable and practical assumptions, it is possible to solve this, otherwise, highly ill-posed problem and recover the $r$ transmitted functions gi and the impulse responses fi in a robust, reliable, and efficient manner, from just one single received function y by solving a semidefinite program. We derive explicit bounds on the number of measurements needed for successful recovery and prove that our method is robust in the presence of noise. Our theory is actually suboptimal, since numerical experiments demonstrate that, quite remarkably, recovery is still possible if the number of measurements is close to the number of degrees of freedom. [ABSTRACT FROM PUBLISHER]

This paper studies the noncausal relay channel, also known as the relay channel with unlimited look ahead, introduced by by El Gamal, Hassanpour, and Mammen. Unlike the standard relay channel model, where the relay encodes its signal based on the previous received output symbols, the relay in the noncausal relay channel encodes its signal as a function of the entire received sequence. In the existing coding schemes, the relay uses this noncausal information solely to recover the transmitted message or part of it and then cooperates with the sender to communicate this message to the receiver. However, it is shown in this paper that by applying the Gelfand–Pinsker coding scheme, the relay can take further advantage of the noncausally available information and achieve rates strictly higher than those of the existing coding schemes. This paper also provides a new upper bound on the capacity of the noncausal relay channel that strictly improves upon the existing cutset bound. These new lower and upper bounds on the capacity coincide for the class of degraded noncausal relay channels and establish the capacity for this class. [ABSTRACT FROM AUTHOR]

Index coding is a source coding problem in which a broadcaster seeks to meet the different demands of several users, each of whom is assumed to have some prior information on the data held by the sender. A well-known application is satellite communications, as described in one of the earliest papers on the subject (Birk and Kol, 1998). It is readily seen that if the sender has knowledge of its clients’ requests and their side-information sets, then the number of packet transmissions required to satisfy all users’ demands can be greatly reduced if the data are encoded before sending. The collection of side-information indices as well as the indices of the requested data is described as an instance \mathcal I of the index coding with side-information (ICSI) problem. The encoding function is called the index code of $ \mathcal I$ , and the number of transmissions, resulting from the encoding is referred to as its length. The main ICSI problem is to determine the optimal length of an index code and instance $ \mathcal I$ . As this number is hard to compute, bounds approximating it are sought, as are algorithms to compute efficient index codes. These questions have been addressed by several authors (e.g., see Alon et al. 2008, Bar-Yossef et al. 2011, Blasiak et al. 2013), often taking a graph-theoretic approach. Two interesting generalizations of the problem that have appeared in the literature are the subject of this paper. The first of these is the case of index coding with coded side information (Dai et al. 2014), in which linear combinations of the source data are both requested by and held as users’ side-information. This generalization has applications, for example, to relay channels and necessitates algebraic rather than combinatorial methods. The second is the introduction of error-correction in the problem, in which the broadcast channel is subject to noise (Dau et al. 2013). In this paper, we characterize the optimal length of a scalar or vector linear index code with coded side information (ICCSI) over a finite field in terms of a generalized min-rank and give bounds on this number based on constructions of random codes for an arbitrary instance. We furthermore consider the length of an optimal $\delta $ -error correcting code for an instance of the ICCSI problem and obtain bounds analogous to those described in (Dau et al. 2013), both for the Hamming metric and for rank-metric errors. We describe decoding algorithms for both categories of errors. [ABSTRACT FROM AUTHOR]

Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. This paper proposes a new paradigm, referred to as many-user information theory, where the number of users is allowed to grow with the blocklength. This paradigm is motivated by emerging systems with a massive number of users in an area, such as the Internet of Things. The focus of this paper is the many-access channel model, which consists of a single receiver and many transmitters, whose number increases unboundedly with the blocklength. Moreover, an unknown subset of transmitters may transmit in a given block and need to be identified as well as decoded by the receiver. A new notion of capacity is introduced and characterized for the Gaussian many-access channel with random user activities. The capacity can be achieved by first detecting the set of active users and then decoding their messages. The minimum cost of identifying the active users is also quantified. [ABSTRACT FROM AUTHOR]

Motivated by the problem of zero-error broadcasting, we introduce a new notion of graph capacity, termed $\rho $ -capacity, that generalizes the Shannon capacity of a graph. We derive upper and lower bounds on the $\rho $ -capacity of arbitrary graphs, and provide a Lovász-type upper bound for regular graphs. We study the behavior of the $\rho $ -capacity under two graph operations: the strong product and the disjoint union. Finally, we investigate the connection between the structure of a graph and its $\rho $ -capacity. [ABSTRACT FROM PUBLISHER]

Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previously known asymptotic achievability and converse results, the energy-distortion exponent, defined as the rate of decay of the square-error distortion as the available energy-to-noise ratio increases without bound, is completely characterized for both the point-to-point and broadcast channel cases. Turning then to the scenario of zero-delay transmission, where outage events with arbitrarily small probability are allowed, it is shown that the same energy-distortion exponent as in the infinite-delay case can be achieved in all the studied scenarios. [ABSTRACT FROM AUTHOR]

We consider an L -user multiple access channel where transmitter m has access to the linear equation \textum =\bigoplus l=1^{L} fml{\text{w}}l of independent messages {\text{w}}l \in \mathbb {F}p^{kl} with fml\in ~\mathbb {F}p , and the destination wishes to recover all $L$ messages. This problem may be motivated as the last hop in a network where relay nodes employ the compute-and-forward strategy and decode linear equations of messages; we seek to do the reverse and extract messages from sums over a multiple access channel. In particular, we exploit the particular form of dependencies between the equations at the different relays to improve the reliable communication rates beyond those achievable by simply forwarding all equations to the destination independently. The presented achievable rate region for the discrete memoryless channel model is shown to be capacity for the additive white Gaussian noise channel. [ABSTRACT FROM PUBLISHER]

We consider the Gaussian wiretap channel, where two legitimate players Alice and Bob communicate over an additive white Gaussian noise (AWGN) channel, while Eve is eavesdropping, also through an AWGN channel. We propose a coding strategy based on lattice coset encoding. We define the secrecy gain as a design criterion for wiretap lattice codes, expressed in terms of the lattice theta series, which characterizes Eve’s confusion as a function of the channel parameters. The secrecy gain is studied for even unimodular lattices, and an asymptotic analysis shows that it grows exponentially in the dimension of the lattice. Examples of wiretap lattice codes are given. [ABSTRACT FROM AUTHOR]