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We consider transmission over the ergodic fading multiple-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at the receiver. Over the equivalent non-fading channel, capacity has recently been shown to be achievable using transmission schemes that were designed for the "dirty paper" channel. We focus on a similar "fading paper" model. The evaluation of the fading paper capacity is difficult to obtain. We confine ourselves to the linear-assignment capacity, which we define, and use convex analysis methods to prove that its maximizing distribution is Gaussian. We compare our fading-paper transmission to an application of dirty paper coding that ignores the partial state information and assumes the channel is fixed at the average fade. We show that a gain is easily achieved by appropriately exploiting the information. We also consider a cooperative upper bound on the sum-rate capacity as suggested by Sato. We present a numeric example that indicates that our scheme is capable of realizing much of this upper bound. [ABSTRACT FROM AUTHOR]

We compare the capacity of dirty-paper coding (DPC) to that of time-division multiple access (TDMA) for a multiple-antenna (multiple- input multiple-output (MIMO)) Gaussian broadcast channel (BC). We find that the sum-rate capacity (achievable using DPC) of the multiple-antenna BC Is at most min(M, K) times the largest single-user capacity (i.e., the TDMA sum-rate) in the system, where M is the number of transmit antennas and K is the number of receivers. This result is Independent of the number of receive antennas and the channel gain matrix, and is valid at all signal-to-noise ratios (SNRs). We investigate the tightness of this bound In a time-varying channel (assuming perfect channel knowledge at receivers and transmitters) where the channel experiences uncorrelated Rayleigh fading and In some situations we find that the dirty paper gain is upper-bounded by the ratio of transmit-to-receive antennas. We also show that min(M, K) upper-bounds the sum-rate gain of successive decoding over TDMA for the uplink channel, where M is the number of receive antennas at the base station and K is the number of transmitters. [ABSTRACT FROM AUTHOR]

This paper develops a methodology for finding minimum energy per bit in networks with correlated information, without at need for finding bounds on capacity. This is used to derive the exact minimum energy per bit for some broadcast and interference channels with common and correlated messages, and bounds on the minimum energy per bit for some other channels. [ABSTRACT FROM PUBLISHER]

Cognitive radio promises a low-cost, highly flexible alternative to the classic single-frequency band, single-protocol wireless device. By sensing and adapting to its environment, such a device is able to fill voids in the wireless spectrum and can dramatically increase spectral efficiency. In this paper, the cognitive radio channel is defined as a two-sender, two-receiver interference channel in which sender 2 obtains the encoded message sender 1 plans to transmit. We consider two cases: in the genie-aided cognitive radio channel, sender 2 is noncausally presented the data to be transmitted by sender 1 while in the causal cognitive radio channel, the data is obtained causally. The cognitive radio at sender 2 may then choose to transmit simultaneously over the same channel, as opposed to waiting for an idle channel as is traditional for a cognitive radio. Our main result is the development of an achievable region which combines Gel'fand-Pinkser coding with an achievable region construction for the interference channel. In the additive Gaussian noise case, this resembles dirty-paper coding, a technique used in the computation of the capacity of the Gaussian multiple-input multiple-output (MIMO) broadcast channel. Numerical evaluation of the region in the Gaussian noise case is performed, and compared to an inner bound, the interference channel, and an outer bound, a modified Gaussian MIMO broadcast channel. Results are also extended to the case in which the message is causally obtained. [ABSTRACT FROM AUTHOR]

We investigate the problem of downlink user scheduling in multiple-input multiple-output (MIMO) systems with M transmit antennas and K homogeneous multiantenna receiving users. We develop a simple algorithm to schedule a subset of M active users for data transmission.We first identify a set of L candidate users that should provide channel information feedback. We then select M active users among the L candidates based on joint consideration of their effective channel gains and directions. We derive an asymptotic upper bound for the sum rate gap between the maximum sum rate of the M selected active users, achieved by dirty paper coding, and the full sum capacity of the original MIMO broadcast channel. Utilizing the upper bound, we show that the sum rate gap can be reduced to meet user requirement by suitably choosing a large but still finite L. Furthermore, we also investigate the performance of the low complexity zero-forcing beamforming (ZFBF) for the M active users. [ABSTRACT FROM AUTHOR]

This correspondence considers communication over two Gaussian channels with additive state interference anti noiseless output feedback-the multiple access channel (MAC) and the augmented broad- cast channel (ABC) (a special class of the physically degraded broadcast channel). The state interference is assumed to be available noncausally at the transmitters. Deterministic coding schemes for these two channels were suggested by Ozarow when there is no state present. Recently, Merhav and Weissman derived an optimal feedback coding scheme for the single-user Gaussian channel with additive state interference. Combining ideas from these two schemes, we extend Ozarow's coding algorithms to the state-dependent case, showing that the capacity regions of the MAC and the ABC are not affected, even though not all parts of the system have knowledge of the state. The proposed schemes attain a better error performance and reduce the coding complexity with respect to the standard random binning coding technique. [ABSTRACT FROM AUTHOR]

In this correspondence, we show that solutions to the multiple description coding problem and the broadcast channel coding problem share a common encoding procedure: successive source encoding. We use this connection as the basis for establishing connections between the achievable multiple description rate region and Marton's region for broadcast channels. Specifically, we show that Marton's encoding scheme can be viewed as a multiple description coding procedure. We also explore the dual problem, namely, the relationship between successive channel decoding in multiple access communication and distributed source coding. By illuminating these connections to multiple description, we hope to motivate a solution to what remains a mostly unsolved problem. [ABSTRACT FROM AUTHOR]

In this paper, we study linear encoding for a pair of correlated Gaussian sources transmitted over a two-user Gaussian broadcast channel in the presence of unit-delay noiseless feedback, abbreviated as the GBCF. Each pair of source samples is transmitted using a linear transmission scheme in a finite number of channel uses. We investigate three linear transmission schemes: A scheme based on the Ozarow–Leung (OL) code, a scheme based on the linear quadratic Gaussian (LQG) code of Ardestanizadeh et al., and a novel scheme derived in this paper using a dynamic programming (DP) approach. For the OL and LQG schemes we present lower and upper bounds on the minimal number of channel uses needed to achieve a target mean-square error (MSE) pair. For the LQG scheme in the symmetric setting, we identify the optimal scaling of the sources, which results in a significant improvement of its finite horizon performance, and, in addition, characterize the (exact) minimal number of channel uses required to achieve a target MSE. Finally, for the symmetric setting, we show that for any fixed and finite number of channel uses, the DP scheme achieves an MSE lower than the MSE achieved by either the LQG or the OL schemes. [ABSTRACT FROM AUTHOR]

Index coding studies multiterminal source-coding problems where a set of receivers are required to decode multiple (possibly different) messages from a common broadcast, and they each know some messages a priori. In this paper, at the receiver end, we consider a special setting where each receiver knows only one message a priori, and each message is known to only one receiver. At the broadcasting end, we consider a generalized setting where there could be multiple senders, and each sender knows a subset of the messages. The senders collaborate to transmit an index code. This paper looks at minimizing the number of total coded bits the senders are required to transmit. When there is only one sender, we propose a pruning algorithm to find a lower bound on the optimal (i.e., the shortest) index codelength, and show that it is achievable by linear index codes. When there are two or more senders, we propose an appending technique to be used in conjunction with the pruning technique to give a lower bound on the optimal index codelength; we also derive an upper bound based on cyclic codes. While the two bounds do not match in general, for the special case where no two distinct senders know any message in common, the bounds match, giving the optimal index codelength. The results are expressed in terms of strongly connected components in directed graphs that represent the index-coding problems. [ABSTRACT FROM AUTHOR]

The Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC) is considered. The dirty-paper coding (DPC) rate region is shown to coincide with the capacity region. To that end, a new notion of an enhanced broadcast channel is introduced and is used jointly with the entropy power inequality, to show that a superposition of Gaussian codes is optimal for the degraded vector broadcast channel and that DPC is optimal for the nondegraded case. Furthermore, the capacity region is characterized under a wide range of input constraints, accounting, as special cases, for the total power and the per-antenna power constraints. [ABSTRACT FROM AUTHOR]

We consider the generalized dirty-paper channel Y = X + S + N, E{X²} ≤ Px, where N is not necessarily Gaussian, and the interference S is known causally or non causally to the transmitter. We derive worst case capacity formulas and strategies for "strong" or arbitrarily varying interference. In the causal side information (SI) case, we develop a capacity formula based on minimum noise entropy strategies. We then show that strategies associated with entropy-constrained quantizers provide lower and upper bounds on the capacity. At high signal-to-noise ratio (SNR) conditions, i.e., if N is weak relative to the power constraint Px, these bounds coincide, the optimum strategies take the form of scalar lattice quantizers, and the capacity loss due to not having S at the receiver is shown to be exactly the "shaping gain" ½ log( ...) ≈ 0.254 bit. We extend the schemes to obtain achievable rates at any SNR and to noncausal SI, by incorporating minimum mean-squared error (MMSE) scaling, and by using k-dimensional lattices. For Gaussian N, the capacity loss of this scheme is upper-bounded by ½ log πeG(Λ), where G(Λ) is the normalized second moment of the lattice. With a proper choice of lattice, the loss goes to zero as the dimension k goes to infinity, in agreement with the results of Costa. These results provide an information-theoretic framework for the study of common communication problems such as precoding for intersymbol interference (ISI) channels and broadcast channels. [ABSTRACT FROM AUTHOR]

This paper studies incremental relay strategies for a two-user Gaussian relay-interference channel with an in-band-reception and out-of-band-transmission relay, where the link between the relay and the two receivers is modelled as a degraded broadcast channel. It is shown that generalized hash-and-forward (GHF) can achieve the capacity region of this channel to within a constant number of bits in a certain weak-relay regime, where the transmitter-to-relay link gains are not unboundedly stronger than the interference links between the transmitters and the receivers. The GHF relaying strategy is ideally suited for the broadcasting relay because it can be implemented in an incremental fashion, i.e., the relay message to one receiver is a degraded version of the message to the other receiver. A generalized-degree-of-freedom (GDoF) analysis in the high signal-to-noise ratio (SNR) regime reveals that in the symmetric channel setting, each common relay bit can improve the sum rate roughly by either one bit or two bits asymptotically depending on the operating regime, and the rate gain can be interpreted as coming solely from the improvement of the common messages rate, or alternatively in the very weak interference regime as solely coming from the rate improvement of the private messages. Further, this paper studies an asymmetric case in which the relay has only a single link to one of the destinations. It is shown that with only one relay-destination link, the approximate capacity region can be established for a larger regime of channel parameters. Further, from a GDoF point of view, the sum-capacity gain due to the relay can now be thought as coming from either signal relaying only or interference forwarding only. [ABSTRACT FROM PUBLISHER]

We consider a graphical approach to index coding. As cycles have been shown to provide coding gain, cycles and cliques (a specific type of overlapping cycles) have been exploited in an existing literature. In this paper, we define a more general form of overlapping cycles, called the interlinked-cycle ( \mathsf IC ) structure, that generalizes cycles and cliques. We propose a scheme, called the interlinked-cycle-cover ( \mathsf ICC ) scheme, that leverages \mathsf IC structures in digraphs to construct scalar linear index codes. We characterize a class of infinitely many digraphs where our proposed scheme is optimal over all linear and non-linear index codes. Consequently, for this class of digraphs, we indirectly prove that scalar linear index codes are optimal. Furthermore, we show that the \mathsf ICC scheme can outperform all the existing graph-based schemes (including partial-clique-cover and fractional-local-chromatic number schemes), and a random-coding scheme (namely, composite coding) for certain graphs. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of broadcasting information in the most efficient manner in a large 2-D ad hoc wireless network at low SNR and under line-of-sight propagation. A new communication scheme is proposed, where source nodes first broadcast their data to the entire network, despite the lack of sufficient available power. The signal’s power is then reinforced via successive back-and-forth beamforming transmissions between different groups of nodes in the network, so that all nodes are able to decode the transmitted information at the end. This scheme is shown to achieve asymptotically the broadcast capacity of the network, which is expressed in terms of the largest singular value of the matrix of fading coefficients between the nodes in the network. A detailed mathematical analysis is then presented to evaluate the asymptotic behavior of this largest singular value. [ABSTRACT FROM PUBLISHER]

This paper considers maximizing the network-wide minimum supported rate in the downlink of a two-cell system, where each base station (BS) is endowed with multiple antennas. This is done for different levels of cell cooperation. At one extreme, we consider single cell processing where the BS is oblivious to the interference it is creating at the other cell. At the other extreme, we consider full cooperative macroscopic beamforming. In between, we consider coordinated beamforming, which takes account of inter-cell interference, but does not require full cooperation between the BSs. We combine elements of Lagrangian duality and large system analysis to obtain limiting SINRs and bit-rates, allowing comparison between the considered schemes. The main contributions of the paper are theorems which provide concise formulas for optimal transmit power, beamforming vectors, and achieved signal to interference and noise ratio (SINR) for the considered schemes. The formulas obtained are valid for the limit in which the number of users per cell, K, and the number of antennas per base station, N, tend to infinity, with fixed ratio \beta=K/N. These theorems also provide expressions for the effective bandwidths occupied by users, and the effective interference caused in the adjacent cell, which allow direct comparisons between the considered schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider a downlink communication system in which a base station (BS) equipped with M antennas and power constraint P communicates with N users each equipped with K receive antennas. It is assumed that the users have perfect channel state information (CSI) of their own channels, while the BS only knows the partial CSI provided by the receivers via a feedback channel. We study the fundamental limits on the amount of feedback required at the BS to achieve the sum-rate capacity of the system (when BS has perfect CSI for all users) in the asymptotic case of N \to \infty , considering various signal to noise ratio (SNR) regimes. The main results of this paper can be expressed as follows. 1) In the fixed-SNR regime (where the SNR does not scale with N) and low-SNR regime (where the SNR is much smaller than 1\over \ln (N)), to achieve the (1 - \varepsilon)-portion of the sum-rate capacity, the total amount of feedback should scale at least with \ln (\varepsilon ^-1). In the fixed-SNR regime, to reduce the gap between the achievable sum rate and the sum-rate capacity of the system (which is defined as the sum-rate gap) to zero, the amount of feedback should scale at least logarithmically with the sum-rate capacity, which is achievable by using the random beam-forming (RBF) scheme proposed by Sharif and Hassibi. In the low-SNR regime, we propose an opportunistic beam-forming (OBF) scheme, which is shown to be asymptotically feedback optimal. 2) In the high-SNR regime (where the SNR grows to infinity as N \to \infty ), the total amount of feedback depends on the number of receive antennas. In particular, to reduce the sum-rate gap to zero in the case of K < M, the amount of feedback in the SNR regime of \ln (P)\over \ln (N) > 1\over M-1, should scale at least logarithmically with the SNR. In the case of K \geq M, the amount of feedback does not need to scale with the SNR. Moreover, we show that RBF is asymptotically feedback optimal in the high-SNR regime. [ABSTRACT FROM AUTHOR]

This paper studies the fundamental properties of broadcasting in multihop wireless networks. Previous studies have shown that, as long as broadcast capacity is concerned, asymptotically optimal broadcasting is possible in wireless multihop networks under very general conditions. However, none of the existing work on broadcast capacity has considered latency in message delivery, which is simply assumed to be finite (but not explicitly bounded). In this paper, the issue of investigating the fundamental properties of broadcast communications for what concerns both capacity and latency using a realistic, SINR-based interference model is investigated. In particular, a novel topological notion of network connectivity is introduced, and it is shown that, if the network satisfies this property, asymptotically optimal broadcast capacity and latency can be achieved simultaneously. The above result holds in the general scenario in which an arbitrary number of broadcast sources arbitrarily share the available (optimal) network capacity. The result presented in this paper is in sharp contrast to similar results obtained for the case of unicast transmissions, where asymptotically optimal latency in message delivery can be achieved only at the expense of asymptotically reducing network capacity. Thus, the results presented in this paper show that scalable broadcasting in multihop wireless networks is, in principle, possible. [ABSTRACT FROM AUTHOR]

Recently, Gallager's bounding techniques have been used to derive tight performance bounds for coded systems in fading channels. Most works in this field have thus far dealt with coherent decoding. This paper develops Gallager bounds for noncoherent systems in fading channels. Unlike coherent decoding, the exact error probability of a noncoherent decoder/detector conditioned on the fading coefficients does not admit a closed-form expression. This difficulty is overcome in this paper by employing the Chernoff technique. Although it weakens the bounds to some extent, the Chernoff technique enables the derivations of the limit-before-average (LBA) bound and Gallager bounds in closed form for noncoherent fading channels. Numerical examples show that the proposed bounds are convergent and are tighter than the conventional union bound. [ABSTRACT FROM AUTHOR]

Self-healing key distribution schemes allow group managers to broadcast session keys to large and dynamic groups of users over unreliable channels. Roughly speaking, even if during a certain session some broadcast messages are lost due to network faults, the self-healing property of the scheme enables each group member to recover the key from the broadcast messages he has received before and after that session. Such schemes are quite suitable in supporting secure communication in wireless networks and mobile wireless ad-hoc networks. Recent papers have focused on self-healing key distribution, and have provided definitions, stated in terms of the entropy function, and some constructions. The contribution of this paper is the following. • We analyze current definitions of self-healing key distribution and, for two of them, we show that no protocol can achieve the definition. • We show that a lower bound on the size of the broadcast message, previously derived, does not hold. • We propose a new definition of self-healing key distribution, and we show that it can be achieved by concrete schemes. • We give some lower bounds on the resources required for implementing such schemes, i.e., user memory storage and communication complexity. We prove that the bounds are tight. [ABSTRACT FROM AUTHOR]

In this correspondence, we consider the problem of. maximizing sum rate of a multiple-antenna Gaussian broadcast channel (BC). It was recently found that dirty-paper coding is capacity achieving for this channel. In order to achieve capacity, the optimal transmission policy (i.e., the optimal transmit covariance structure) given the channel conditions and power constraint must be found. However, obtaining the optimal transmission policy when employing dirty-paper coding is a computationally complex nonconvex problem. We use duality to transform this problem into a well-structured convex multiple-access channel (MAC) problem. We exploit the structure of this problem and derive simple and fast iterative algorithms that provide the optimum transmission policies for the MAC, which can easily be mapped to the optimal BC policies. [ABSTRACT FROM AUTHOR]

In multiple-antenna broadcast channels, unlike point-to-point multiple-antenna channels, the multiuser capacity depends heavily on whether the transmitter knows the channel coefficients to each user. For instance, in a Gaussian broadcast channel with M transmit antennas and n single-antenna users, the sum rate capacity scales like M log log n for large n if perfect channel state information (CSI) is available at the transmitter, yet only logarithmically with M if it is not. In systems with large n, obtaining full CSI from all users may not be feasible. Since lack of CSI does not lead to multiuser gains, it is therefore of interest to investigate transmission schemes that employ only partial CSI. In this paper, we propose a scheme that constructs M random beams and that transmits information to the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. For fixed M and n increasing, the throughput of our scheme scales as M log log nN, where N is the number of receive antennas of each user. This is precisely the same scaling obtained with perfect CSI using dirty paper coding. We furthermore show that a linear increase in throughput with M can be obtained provided that M does not not grow faster than log n. We also study the fairness of our scheduling in a heterogeneous network and show that, when M is large enough, the system becomes interference dominated and the probability of transmitting to any user converges to &frac1n;, irrespective of its path loss. In fact, using M = α log n transmit antennas emerges as a desirable operating point, both in terms of providing linear scaling of the throughput with M as well as in guaranteeing fairness. [ABSTRACT FROM AUTHOR]

This paper characterizes the sum capacity of a class of potentially nondegraded Gaussian vector broadcast channels where a single transmitter with multiple transmit terminals sends independent information to multiple receivers. Coordination is allowed among the transmit terminals, but not among the receive terminals. The sum capacity is shown to be a saddle-point of a Gaussian mutual information game, where a signal player chooses a transmit covariance matrix to maximize the mutual information and a fictitious noise player chooses a noise correlation to minimize the mutual information. The sum capacity is achieved using a precoding strategy for Gaussian channels with additive side information noncausally known at the transmitter. The optimal precoding structure is shown to correspond to a decision-feedback equalizer that decomposes the broadcast channel into a series of single-user channels with interference pre-subtracted at the transmitter. [ABSTRACT FROM AUTHOR]

A (layered) broadcast approach is studied for the fading wiretap channel without the channel state information (CSI) at the transmitter. Two broadcast schemes, based on superposition coding and embedded coding, respectively, are developed to encode information into a number of layers and use stochastic encoding to keep the corresponding information secret from an eavesdropper. The layers that can be successfully and securely transmitted are determined by the channel states to the legitimate receiver and the eavesdropper. The advantage of these broadcast approaches is that the transmitter does not need to know the CSI to the legitimate receiver and the eavesdropper, but the scheme still adapts to the channel states of the legitimate receiver and the eavesdropper. Three scenarios of block fading wiretap channels with stringent delay constraints are studied, in which either the legitimate receiver's channel, the eavesdropper's channel, or both channels are fading. For each scenario, the secrecy rate that can be achieved via the broadcast approach developed in this paper is derived, and the optimal power allocation over the layers (or the conditions on the optimal power allocation) is also characterized. A notion of probabilistic secrecy, which characterizes the probability that a certain secrecy rate of decoded messages is achieved during one block, is also introduced and studied for scenarios when the eavesdropper's channel is fading. Numerical examples are provided to demonstrate the impact of the CSI at the transmitter and the channel fluctuations of the eavesdropper on the average secrecy rate. These examples also demonstrate the advantage of the proposed broadcast approach over the compound channel approach. [ABSTRACT FROM AUTHOR]

This paper considers a Gaussian broadcast channel with two unmatched degraded components, three individual messages, and a common message that is intended for all three receivers. It is shown that for this channel, superposition coding with Gaussian signalling is sufficient to achieve every point in the capacity region. [ABSTRACT FROM AUTHOR]

With progressive image or scalable video encoders, as more bits are received, the source can be reconstructed with progressively better quality. These progressive codes have gradual differences of importance in their bitstreams, which necessitates multiple levels of unequal error protection (UEP). One practical method of achieving UEP is based on a constellation of nonuniformly spaced signal points, or hierarchical constellations. However, hierarchical modulation can achieve only a limited number of UEP levels for a given constellation size. Though hierarchical modulation has been intensively studied for digital broadcasting or multimedia transmission, most work has considered only two layered source coding, and methods of achieving a large number of UEP levels for progressive transmission have rarely been studied. In this paper, we propose a multilevel UEP system using multiplexed hierarchical quadrature amplitude modulation (QAM). We show that multiple levels of UEP are achieved by the proposed multiplexing method. When the BER is dominated by the minimum Euclidian distance, we derive an optimal multiplexing approach which minimizes both the average and peak powers. We next propose an asymmetric hierarchical QAM which reduces the peak-to-average power ratio (PAPR) of the proposed UEP system without any performance loss. Numerical results show that the performance of progressive transmission over Rayleigh fading channels is significantly enhanced by the proposed methods. [ABSTRACT FROM AUTHOR]

This paper proposes a generalized sequential slotted amplify and forward (GSSAF) strategy for single-antenna wireless cooperative networks. The diversity and multiplexing tradeoff (DMT) is analyzed. Applications to cooperative multiple relay channels, cooperative broadcast channels (CBC) and cooperative multiple access channels are considered and the DMT upper bound is proven to be achievable for each case. Other than proposing the best known near-optimal strategy for CBC, another important contribution is to show that GSSAF can be used as a unified strategy to achieve DMT optimality in wireless cooperative networks with unit multiplexing gains. [ABSTRACT FROM AUTHOR]

In this paper, we consider the discrete, time-varying broadcast channel (BC) with memory under the assumption that the channel states belong to a set of finite cardinality. We study the achievable rates in several scenarios of feedback and full unidirectional receiver cooperation. In particular, we focus on two scenarios: the first scenario is the general finite-state broadcast channel (FSBC) where both receivers send feedback to the transmitter while one receiver also sends its channel output to the second receiver. The second scenario is the degraded FSBC where only the strong receiver sends feedback to the transmitter. Using a superposition codebook construction, we derive the capacity regions for both scenarios. Combining elements from these two basic results, we obtain the capacity regions for a number of additional broadcast scenarios with feedback and unidirectional receiver cooperation. [ABSTRACT FROM PUBLISHER]

A fundamental problem in wireless networks is determining the broadcast capacity, i.e., the maximum data transfer rate from a given node to every other node in a relay network. This paper studies the scaling of the broadcast capacity for a network with a single source and N destinations, of which ƒ (N) are randomly selected to also act as relays. In high-density networks (i.e., the node density goes to infinity; the network area is fixed), it is shown that the broadcast capacity is upper bounded by Θ(log ƒ(N)). Schemes are provided that achieve i) Θ(log ƒ(N)) throughput if the channel fading is spatially continuous; ii) Θ(log log ƒ(N)) throughput if the channel fading is spatially i.i.d.. For extended networks (i.e., the node density is fixed; the network area goes to infinity), the broadcast capacity is upper bounded by Θ(1) under channel models with fading and path-loss exponent α > 2. A multistage cooperative broadcasting scheme, which achieves Θ(1) broadcast rate for the high-density extended networks with pathloss channel model is proposed. These results quantifies the gains obtained due to cooperation compared to multihop noncooperative broadcasting, which has a maximum rate that scales as Θ(1) for high-density and Θ(1/(log ƒ(N))α/2) for extended networks. [ABSTRACT FROM AUTHOR]

This paper introduces the notions of variable-to-fixed and fixed-to-variable channel capacity, without feedback. For channels that satisfy the strong converse, these notions coincide with the conventional Shannon capacity. For channels that do not behave ergodically, the conventional fixed-rate Shannon capacity only depends on least-favorable channel conditions, while the variable-rate capacity notions are able to capture the whole range of channel states and their likelihood, even in the absence of any side information about channel state at the transmitter. Particular emphasis is placed on memoryless channels that are governed by finitely valued states. We show that (single-user) variable-to-fixed channel capacity is intimately connected to the capacity region of broadcast channels with degraded message sets, and we give an expression for the fixed-to-variable capacity. [ABSTRACT FROM AUTHOR]

In this paper, a downlink system in which a single-antenna base station communicates with K single antenna users over a time-correlated fading channel is considered. It is assumed that each receiver knows its own channel state, while the rate of the channel variation for all users and the corresponding initial fading gains are known to the base station. The average (per channel use throughput of the system is studied by applying various adaptive signaling schemes. Assuming a large number of users in the system, it is shown that using a scheduling scheme in which the base station transmits to the user with the maximum initial fading gain while using a fixed codeword length for all users, achieves the order of the maximum throughput. Moreover, an alternative scheduling scheme is proposed (by accounting for users' delays) and shown to achieve the optimum long-term fairness, while preserving the order of the maximum throughput. [ABSTRACT FROM AUTHOR]

This paper studies capacity bounds for discrete memoryless broadcast channels with confidential messages. Two private messages as well as a common message are transmitted; the common message is to be decoded by both receivers, while each private message is only for its intended receiver. In addition, each private message is to be kept secret from the unintended receiver where secrecy is measured by equivocation. Both inner and outer bounds are proposed to the rate equivocation region for broadcast channels with confidential messages. The proposed inner bound generalizes Csiszár and Körner's rate equivocation region for broadcast channels with a single confidential message, Liu et al.'s achievable rate region for broadcast channels with perfect secrecy Marton's and Gel'fand-Pinsker's achievable rate region for general broadcast channels. The proposed outer bounds, together with the inner bound, help establish the rate equivocation region of several classes of discrete memoryless broadcast channels with confidential messages, including the less noisy, deterministic, and semideterministic broadcast channels. Furthermore, specializing to the general broadcast channel by removing the confidentiality constraint, the proposed outer bounds reduce to new capacity outer bounds for the discrete memory broadcast channel. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the general relay channel. We investigate the application of the estimate-and-forward (EAF) relaying scheme to different scenarios. Specifically, we study assignments of the auxiliary random variable that always satisfy the feasibility constraints. We then consider the Gaussian relay channel with coded modulation, where we show that a three-level quantization outperforms the Gaussian quantization commonly used to evaluate the achievable EAF rates in this scenario. Last, we consider the cooperative general broadcast scenario with a multistep conference between the receivers. We first apply EAF to obtain a general achievable rate region with a multistep conference. We then use an explicit assignment for the auxiliary random variables to obtain an explicit rate expression for the single common message case with a two-step conference. [ABSTRACT FROM AUTHOR]

In a multiple-antenna system with two transmitters and two receivers, a scenario of data communication, known as the X channel, is studied in which each receiver receives data from both transmitters. In this scenario, it is assumed that each transmitter is unaware of the other transmitter's data (noncooperative scenario). This system can be considered as a combination of two broadcast channels (from the transmitters' points of view) and two multiple-access channels (from the receivers' points of view). Taking advantage of both perspectives, two signaling schemes for such a scenario are developed. In these schemes, some linear filters are employed at the transmitters and at the receivers which decompose the system into either two noninterfering multiple-antenna broadcast subchannels or two noninterfering multiple-antenna multiple. access subchannels. The main objective in the design of the filters is to exploit the structure of the channel matrices to achieve the highest multiplexing gain (MG). It is shown that the proposed noncooperative signaling schemes outperform other known noncooperative schemes in terms of the achievable MG. In particular, it is shown that in some specific cases, the achieved MG is the same as the MG of the system if full cooperation is provided either between the transmitters or between the receivers. In the second part of the paper, it is shown that by using mixed design schemes, rather than decomposition schemes, and taking the statistical properties of the interference terms into account, the power offset of the system can be improved. The power offset represents the horizontal shift in the curve of the sum-rate versus the total power in decibels. [ABSTRACT FROM AUTHOR]

In this paper, we consider a graph-based framework for transmission of correlated sources over multiple-access channels. It is well known that the separation approach is not optimal for this multiuser communication. Our objective in this work is to reintroduce modularity in this problem using a graph-based discrete interface and to minimize the performance loss as compared to the optimal joint source-channel coding scheme. The proposed framework envisages a transmission systems with two modules: a source-coding module and a channel-coding module. In the former module, the correlated sources are encoded distributively into correlated messages whose correlation structure can be associated with a bipartite graph. These correlated messages are then encoded by using correlated codewords and are reliably transmitted over the multiple-access channel -in the latter module. This leads to performance gains in terms of enlarging the class of correlated sources that can be reliably transmitted over a multiple-access channel as compared to the conventional separation approach. We provide an information-theoretic characterization of 1) the rate of exponential growth (as a function of the number of channel uses) of the size of the bipartite graphs whose edges can be reliably transmitted over a multiuser channel and 2) the rate of exponential growth (as a function of the number of source samples) of the size of the bipartite graphs which can reliably represent a pair of correlated sources to be transmitted over a multiuser channel. [ABSTRACT FROM AUTHOR]

In this paper, a low-complexity cooperative protocol that significantly increases the average throughput of multihop upstream transmissions for wireless tree networks is developed and analyzed. A system in which transmissions are assigned to nodes in a collision free, spatial time division fashion is considered. The suggested protocol exploits the broadcast nature of wireless networks where the communication channel is shared between multiple adjacent nodes within interference range. For any upstream end-to-end flow in the tree, each intermediate node receives information from both one-hop and two-hop neighbors and transmits only sufficient information such that the next upstream one-hop neighbor will he able to decode the packet. This approach can be viewed as the generalization of the classical three node relay channel for end-to-end flows in which each intermediate node becomes successively source, relay and destination. The achievable rate for any regular tree network is derived and an optional schedule that realizes this rate in most cases is proposed. Our protocol is shown to dramatically outperform the conventional scheme where intermediate nodes simply forward the packets hop by hop. At high signal-to-noise ratio (SNR), it yields approximately 66% throughput gain for practical scenarios. [ABSTRACT FROM AUTHOR]

We consider the problem of communicating over the general discrete memoryless broadcast channel (DMBC) with partially cooperating receivers. In our setup, receivers are able to exchange messages over noiseless conference links of finite capacities, prior to decoding the messages sent from the transmitter. In this paper, we formulate the general problem of broadcast with cooperation. We first find the capacity region for the case where the BC is physically degraded. Then, we give achievability results for the general broadcast channel, for both the two independent messages case and the single common message case. [ABSTRACT FROM AUTHOR]

Contemporary wireless systems combine aspects of network theory such as scheduling, throughput, and delay as well as information theory aspects such as capacity, coding, and power control. Design of such systems requires joint optimization of both network and physical layers. In this paper, we analyze a single-user communication system composed of a transmitter preceded by a queue used for retransmissions, Gaussian block-fading channel, and a receiver. The system average delay is optimized by using combined power/rate control under average power constraints. Dynamic programming is used for calculating the optimized policies using numerical analysis as well as analytic analysis for asymptotically large buffer size. Asymptotic results are obtained for all combinations of fixed or variable power and rate controls. The most important result extends the "water-filling" result for systems with average delay constraint. [ABSTRACT FROM AUTHOR]

A wireless sensory relay network consists of one source node, one destination node and multiple intermediate relay nodes. In this paper, we study the achievable rates and the scaling laws of power-constrained wireless relay networks in the wideband regime, assuming that relay nodes have no a priori knowledge of channel-state information (CSI) for both the backward channels and the forward channels. We examine the achievable rates in the joint asymptotic regime of the number of relay nodes n, the channel coherence interval L, and the bandwidth W (or the SNR per link ρ). We first study narrowband relay networks in the low SNR regime. We investigate a relaying scheme, namely amplify-and-forward (AF) with network training, in which the source node and the destination node broadcast training symbols and each relay node carries out channel estimation and then applies AF relaying to relay information. We provide an equivalent source-to-destination channel model, and characterize the corresponding achievable rate. Our findings show that when ρL, proportional to the transmission energy in each fading block, is bounded below, the achievable rate has the same scaling order as in coherent relaying, thus enabling us to characterize the scaling law of the relay networks in the low SNR regime. We then generalize the study to power-constrained wideband relay networks, where frequency-selective fading is taken into account. Again, the focus is on the achievable rates by using AF with network training for information relaying. In particular, we examine the scaling behavior of the achievable rates corresponding to two power allocation policies across the frequency subbands at relay nodes, namely, a simple equal power allocation policy and the optimal power allocation policy. We identify the conditions under which the scaling law of the wideband relay networks can be achieved by both power allocation policies. Somewhat surprising, our findings indicate that these two power allocation policies result in achievable rates of the same scaling order, and the scaling law can be characterized under the condition that L/W, proportional to the energy per fading block per subband, is bounded below, and that W is sublinear in n. [ABSTRACT FROM AUTHOR]

We consider multiaccess, broadcast, and interference channels with additive Gaussian noise. Although the set of rate pairs achievable by time-division multiple access (TDMA) is not equal to the capacity region, the TDMA achievable region converges to the capacity region as the power decreases. Furthermore, TDMA achieves the optimum minimum energy per bit. Despite those features, this paper shows that the growth of TDMA-achievable rates with the energy per bit is suboptimal in the low-power regime except in special cases: multiaccess channels where the users' energy per bit are identical and broadcast channels where the receivers have identical signal-to-noise ratios. For the additive Giussian noise interference channel, we identify a small region of interference parameters outside of which TDMA is also shown to be suboptimal. The effect of fading (known to the receiver) on the suboptimality of TDMA is also explored. [ABSTRACT FROM AUTHOR]

Considers a multiuser multiple-input multiple-output (MIMO) Gaussian broadcast channel, where the transmitter and receivers have multiple antennas. MIMO capacity region; Computational complexity required for obtaining the dirty paper achievable region.

A new hybrid digital/analog scheme is proposed for lossy transmission of a Gaussian source over a bandwidth-matched Gaussian broadcast channel with source side information available at each receiver. The proposed scheme combines two schemes that were previously shown to achieve optimal point-to-point distortion/power tradeoff simultaneously at all receivers under two distinct conditions stated in terms of channel and side information quality parameters. For the two-receiver case, the combined scheme is shown to achieve the same kind of optimality for the entire region in the parameter space sandwiched between those two conditions. Crucial to this result is a new degree of freedom discovered in designing point-to-point hybrid digital/analog schemes with side information. When superimposed with analog transmission, the proposed scheme outperforms all previously known schemes even outside the optimality region in the parameter space. [ABSTRACT FROM AUTHOR]

The relay broadcast channel (RBC) models a system where a transmitter sends information to multiple receivers, aided by the presence of a dedicated relay node. In the Gaussian case with two receivers, under the assumption that both receivers are degraded with respect to the relay, it is shown that the capacity region is achieved by a superposition strategy. This strategy is also shown to be optimal in the case where there is feedback from the receivers to the relay and one receiver assumed to be degraded with respect to the other in an appropriate sense. We also present an achievable region for a more general Gaussian RBC (GRBC) model. [ABSTRACT FROM AUTHOR]