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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]

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 the block diagonalization (BD) and user selection based on limited feedback in multiple antenna broadcast channels. With limited feedback, due to the imperfect channel state information at the transmitter (CSIT), BD cannot completely eliminate multiuser interference, and the throughput is correspondingly lower than that achieved with perfect CSIT. Nevertheless, the achievable multiuser diversity gain can be the same, such that limited-feedback-based BD can achieve an optimal throughput growth as the number of users increases. To show this, we first propose a channel quality indicator (CQI) for user selection. The CQI is designed to accurately estimate an achievable rate of each user and is given by an expected rate, where the expectation is solely taken over precoding matrices which cannot be known at the feedback stage. With the proper CQI, user selection can benefit from a large number of users in the system. As a result, we show that the BD can achieve an asymptotically optimal growth in throughput with the proposed CQI, based solely on a finite-rate feedback of channel information. [ABSTRACT FROM PUBLISHER]

A class of diamond networks is studied where the broadcast component is orthogonal and modeled by two independent bit-pipes. New upper and lower bounds on the capacity are derived. The proof technique for the upper bound generalizes the bounding techniques of Ozarow for the Gaussian multiple description problem (1981) and Kang and Liu for the Gaussian diamond network (2011). The lower bound is based on Marton’s coding technique and superposition coding. The bounds are evaluated for Gaussian and binary adder multiple access channels (MACs). For Gaussian MACs, both the lower and upper bounds strengthen the Kang–Liu bounds and establish capacity for interesting ranges of bit-pipe capacities. For binary adder MACs, the capacity is established for all the ranges of bit-pipe capacities. [ABSTRACT FROM PUBLISHER]

In this paper, we study the information theoretic maximal degrees of freedom (DoF) for the symmetric multi-input–multi-output (MIMO) interfering broadcast channel (IBC) with arbitrary antenna configurations. For the G-cell K-user M\times N MIMO-IBC network, we find that the information theoretic maximal DoF per user are related to three DoF bounds: 1) the decomposition DoF bound , a lower-bound of asymptotic IA; 2) the proper DoF bound d^{\rm{Proper}}=(M+N)/(GK+1), an upper-bound of linear IA; and 3) the quantity DoF bound d^{\rm{Quan}}$ , a zigzag piecewise linear function of M$ and N$. For most configurations in Region I where , the maximal DoF are the decomposition DoF bound and achieved by the asymptotic IA. For all configurations in Region II where \mathcal{R}^{\rm{II}}=\lbrace M/N | d^{\rm{Proper}} \geq d^{\mathrm{Decom}}\rbrace , the maximal DoF are the quantity DoF bound and achieved by the linear IA. To obtain the tight upper-bound, we propose a unified way to construct genies to help each base station or user resolve the maximal number of interference. According to the feature that the designed genies with the same dimension can derive identical DoF upper-bound, we convert the information theoretic DoF upper-bound problem into a linear algebra problem and obtain the closed-form DoF upper-bound expression. Moreover, we develop a non-iterative linear IA transceiver to achieve the DoF upper-bound for antenna configurations in Region II. The basic principles to derive the DoF upper-bound and design the linear IA transceiver to achieve the DoF upper-bound can be extended into general asymmetric networks. [ABSTRACT FROM PUBLISHER]

We consider the problem of joint recovery of a bivariate Gaussian source and of interference over the two-user Gaussian degraded broadcast channel in the presence of common interference. The interference, that is available non-causally at the encoder, is assumed to be Gaussian and correlated to the sources. The tradeoff between the distortion of the sources and the interference estimation error is studied; information-theoretic outer and inner bounds based on ideas from rate-distortion theory and hybrid coding are derived, respectively. More precisely, the outer bound is found by assuming additional knowledge at each user; the inner bound, however, is obtained by analyzing the distortion of a layered hybrid scheme based on proper power splitting, Costa and Wyner–Ziv coding. Low delay and complexity coding schemes based on analog mapping are next proposed. More specifically, parametric mappings based on linear and sawtooth curves are studied and optimized by minimizing an upper bound on the system’s distortion; nonparametric mappings based on joint optimization between the encoder and the decoder using an iterative algorithm are designed. Numerical results show that for the special cases that are previously considered by Abou Saleh et al. (with no fading), the derived outer bound is tighter and the proposed hybrid scheme has a lower complex structure with no loss in performance. In addition, the proposed low delay nonlinear schemes outperform the linear scheme and perform relatively close to the inner bound under certain system settings. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a radio frequency (RF) lens-embedded massive multiple-input multiple-output (MIMO) system and evaluate the system performance of limited feedback by utilizing a technique for generating a suitable codebook for the system. We fabricate an RF lens that operates on a 77-GHz (millimeter-wave) band. Experimental results show a proper value of amplitude gain and an appropriate focusing property. In addition, using a simple numerical technique—beam propagation method—we estimate the power profile of the RF lens and verify its accordance with experimental results. We also design a codebook—multivariance codebook quantization—for limited feedback by considering the characteristics of the RF lens antenna for massive MIMO systems. Numerical results confirm that the proposed system shows significant performance enhancement over a conventional massive MIMO system without an RF lens. [ABSTRACT FROM PUBLISHER]

The binary symmetric stochastic block model deals with a random graph of $n$ vertices partitioned into two equal-sized clusters, such that each pair of vertices is independently connected with probability $p$ within clusters and $q$ across clusters. In the asymptotic regime of $p=a \log n/n$ and $q=b \log n/n$ for fixed $a,b$ , and $n \to \infty $ , we show that the semidefinite programming relaxation of the maximum likelihood estimator achieves the optimal threshold for exactly recovering the partition from the graph with probability tending to one, resolving a conjecture of Abbe et al. Furthermore, we show that the semidefinite programming relaxation also achieves the optimal recovery threshold in the planted dense subgraph model containing a single cluster of size proportional to $n$ . [ABSTRACT FROM AUTHOR]

The quantum relative entropy between two states satisfies a monotonicity property meaning that applying the same quantum channel to both states can never increase their relative entropy. It is known that this inequality is only tight when there is a recovery map that exactly reverses the effects of the quantum channel on both states. In this paper, we strengthen this inequality by showing that the difference of relative entropies is bounded below by the measured relative entropy between the first state and a recovered state from its processed version. The recovery map is a convex combination of rotated Petz recovery maps and perfectly reverses the quantum channel on the second state. As a special case, we reproduce recent lower bounds on the conditional mutual information, such as the one proved by Fawzi and Renner. Our proof only relies on the elementary properties of pinching maps and the operator logarithm. [ABSTRACT FROM AUTHOR]

Linear network coding transmits data through networks by letting the intermediate nodes combine the messages they receive and forward the combinations toward their destinations. The solvability problem asks whether the demands of all the destinations can be simultaneously satisfied by using linear network coding. The guessing number approach converts this problem into determining the number of fixed points of coding functions f:A^n\to A^n over a finite alphabet $A$ (usually referred to as Boolean networks if A = \{0,1\} ) with a given interaction graph that describes which local functions depend on which variables. In this paper, we generalize the so-called reduction of coding functions in order to eliminate variables. We then determine the maximum number of fixed points of a fully reduced coding function, whose interaction graph has a loop on every vertex. Since the reduction preserves the number of fixed points, we then apply these ideas and results to obtain four main results on the linear network coding solvability problem. First, we prove that non-decreasing coding functions cannot solve any more instances than routing already does. Second, we show that the triangle-free undirected graphs are linearly solvable if and only if they are solvable by routing. This is the first classification result for the linear network coding solvability problem. Third, we exhibit a new class of non-linearly solvable graphs. Fourth, we determine large classes of strictly linearly solvable graphs. [ABSTRACT FROM AUTHOR]

We consider the concept of faster-than-Nyquist rate (FTN) broadcasting, which nonorthogonally multiplexes more than one user message in the continuous-time domain for transmission over broadcast channels. Two FTN broadcasting approaches, namely, sub-FTN and full-FTN, are considered for broadcasting of $K$ independent messages over $K$-user continuous time Gaussian broadcast channel. The derived achievable rate regions of the two approaches are shown to be, in general, greater than the capacity region of the optimally coded Nyquist-rate broadcasting using a same modulating pulse. The full-FTN broadcasting provides larger degrees of freedom (capacity pre-log factor) to each user of the broadcast channel while the sub-FTN improves signal-to-interference-plus-noise-ratios of the individual link. The amount of capacity gains in high SNR regime is linearly proportional to excess bandwidth in the modulating pulse used and dependent on FTN signaling rates, channel SNRs, and number of users in the broadcast channel. The simulated sub-FTN and full-FTN broadcast transceivers outperform coded Nyquist-rate systems both in BER performances and in capacity. [ABSTRACT FROM AUTHOR]

We consider two-user MIMO broadcast and interference channels in which confidential messages intended for each receiver are kept secret from the other receiver. The confidential secrecy rates are nonconvex functions of transmit covariance matrices, which makes it intractable to find optimal transmit covariance matrices analytically. In the MIMO broadcast channels, we prove the weighted secrecy sum rate maximization has zero duality gap and KKT conditions are necessary conditions for the optimal solution. We apply the block successive lower-bound maximization technique to nonconvex weighted secrecy sum rate maximization problems. We also derive numerical algorithms for MIMO interference channels and Gaussian wiretap channels with a cooperative jammer. Every limit point achieved by the proposed algorithms is a local optimal solution that satisfies the KKT conditions. Numerical results show that the proposed algorithms outperform existing suboptimal algorithms in terms of secrecy rates. [ABSTRACT FROM PUBLISHER]

We present two approaches for transmitting classical information over quantum broadcast channels. The first technique is a quantum generalization of the superposition coding scheme for the classical broadcast channel. We use a quantum simultaneous nonunique decoder and obtain a proof of the rate region stated in Yard et al., IEEE Trans. Inf. Theory 57 (10), 2011. Our second result is a quantum generalization of the Marton coding scheme. The error analysis for the quantum Marton region makes use of ideas in our earlier work and an idea recently presented by Radhakrishnan et al. in arXiv:1410.3248. Both results exploit recent advances in quantum simultaneous decoding developed in the context of quantum interference channels. [ABSTRACT FROM PUBLISHER]

In wireless push-based systems traffic is asymmetric meaning that the server has much more bandwidth available, as compared to the clients. Since it is often not possible or desirable for the clients to send any requests, the server should broadcast the data periodically. The performance of this system relies heavily on the proper scheduling of the broadcast data. The well known algorithm proposed by Vaidya and Hameed battles this challenge and achieves state-of-the-art performance. However, this performance comes with a computational complexity linear to the number of data items that are broadcast. Furthermore, Vaidya’s and Hameed’s proposed solution for this time complexity degenerates performance. This paper proposes a scheduling algorithm for wireless push-based data broadcasting systems, which performs near optimal and has low computational complexity. Performance evaluation results are presented to demonstrate its efficient performance despite its low computational demands. [ABSTRACT FROM PUBLISHER]

Polar codes are introduced for discrete memoryless broadcast channels. For m -user deterministic broadcast channels, polarization is applied to map uniformly random message bits from m -independent messages to one codeword while satisfying broadcast constraints. The polarization-based codes achieve rates on the boundary of the private-message capacity region. For two-user noisy broadcast channels, polar implementations are presented for two information-theoretic schemes: 1) Cover’s superposition codes and 2) Marton’s codes. Due to the structure of polarization, constraints on the auxiliary and channel-input distributions are identified to ensure proper alignment of polarization indices in the multiuser setting. The codes achieve rates on the capacity boundary of a few classes of broadcast channels (e.g., binary-input stochastically degraded). The complexity of encoding and decoding is O(n \log n) , where n of the average block error probability where 0 < \beta < {1}/{2} . Reproducible experiments for finite block lengths n = 512, 1024, 2048$ corroborate the theory. [ABSTRACT FROM AUTHOR]

Content delivery in a multi-user cache-aided broadcast network is studied, where a server holding a database of correlated contents communicates with the users over a Gaussian broadcast channel (BC). The minimum transmission power required to satisfy all possible demand combinations is studied, when the users are equipped with caches of equal size. Two centralized caching schemes are proposed, both of which not only utilize the user’s local caches, but also exploit the correlation among the contents in the database. The first scheme implements uncoded cache placement and delivers coded contents to users using superposition coding. The second scheme, which is proposed for small cache sizes, places coded contents in users’ caches and jointly encodes the cached contents of users and the messages targeted at them. The performance of the proposed schemes, which provide upper bounds on the required transmit power for a given cache capacity, is characterized. The scheme based on coded placement improves upon the first one for small cache sizes, and under certain conditions meets the uncoded placement lower bound. A lower bound on the required transmit power is also presented assuming uncoded cache placement. Our results indicate that exploiting the correlations among the contents in a cache-aided Gaussian BC can provide significant energy savings. [ABSTRACT FROM AUTHOR]

This paper considers a scenario for multi-user multi-input multi-output (MIMO) communication systems when perfect channel state information at the transmitter (CSIT) is given while the equivalent channel state information at the receiver (CSIR) is not available. Such an assumption is valid for the downlink multi-user MIMO systems with linear precoders that depend on channels to all receivers. We propose a concept called dual systems with zero-forcing design based on the duality principle, originally proposed to relate the Gaussian multi-access channel (MAC) and the Gaussian broadcast channel (BC). For the K-user Nx 2 MIMO BC with N antennas at the transmitter and two antennas at each of the K receivers, we design a downlink interference cancellation (IC) transmission scheme by obtaining the dual of uplink MAC systems employing IC methods. The transmitter simultaneously sends K precoded Alamouti codes, one for each user. Each receiver zero-forces the unintended user's Alamouti codes and decouples its own data streams using two simple linear operations independent of CSIR. Analysis shows that the proposed scheme achieves a diversity gain of 2(N-K+1) for equal energy constellations with short-term power and rate constraints. Power allocation among K users can also be performed to improve the array gain but not the diversity gain. Numerical results demonstrate that the bit error rate of the downlink IC scheme has a diversity gain improvement compared to the block diagonalization (BD) method, which requires global channel information at each node. [ABSTRACT FROM PUBLISHER]

The problem of merging multiple services over multiple-input multiple-output Gaussian broadcast channels with two receivers is studied. The transmitter provides two independent services: a public (multicast) service with a common message for both users, and a private service with a confidential message intended only for one of the users which is to be kept secret from the other. Under this scenario, a new linear precoding scheme is developed to maximize secrecy-multicast rate region. This scheme decomposes input covariance matrix using rotation matrices and results in a reformulation of the secrecy-multicast capacity region which is easier to be optimized. Next, by finding the distributions to which eigenvalues and rotation angles fit in, a search algorithm is proposed to solve the new capacity expression to find precoding and power allocation matrices. Numerical results illustrate that the proposed precoding method significantly increases the rate region compared to the existing methods. [ABSTRACT FROM AUTHOR]

We consider the broadcasting of a scalar memoryless Gaussian source over a two-user Gaussian broadcast channel with bandwidth expansion. In concurrent with the source description, a message that should be decoded reliably just by the “higher quality” user is sent. Conditioned on the message rate, we derive a necessary condition for the achievability of a mean-squared-error distortion pair at the two receivers, which extends the Reznic–Feder–Zamir bound. This necessary condition and a sufficient condition that we derive establish the set of achievable energy-distortion exponents for this setting. [ABSTRACT FROM AUTHOR]

We consider the cache-aided MISO broadcast channel (BC) in which a multi-antenna transmitter serves $K$ single-antenna receivers, each equipped with a cache memory. The transmitter has access to partial knowledge of the channel state information. For a symmetric setting, in terms of channel strength levels, partial channel knowledge levels and cache sizes, we characterize the generalized degrees of freedom (GDoF) up to a constant multiplicative factor. The achievability scheme exploits the interplay between spatial multiplexing gains and coded-multicasting gain. On the other hand, a cut-set-based argument in conjunction with a GDoF outer bound for a parallel MISO BC under channel uncertainty is used for the converse. We further show that the characterized order-optimal GDoF is also attained in a decentralized setting, where no coordination is required for content placement in the caches. [ABSTRACT FROM AUTHOR]

A Gaussian source and two data streams are to be transmitted over a Gaussian broadcast channel: the first stream, the “common stream,” is to be decoded by both receivers, and the second, the “private stream,” only by the strong receiver. Both receivers wish to estimate the source sequence, though with possibly different mean squared-errors. The quadruples of achievable rates and estimation errors are characterized, and it is shown that—once the data rates have been fixed—there is no tension between the estimation errors. Only the “equal bandwidth” case is treated, where the rate at which the source emits symbols is also the rate at which the channel is used. [ABSTRACT FROM AUTHOR]

An analogy framework between wiretap channels (WTCs) and state-dependent point-to-point channels with non-causal encoder channel state information (referred to as Gelfand-Pinker channels (GPCs)) is proposed. A good sequence of stealth-wiretap codes is shown to induce a good sequence of codes for a corresponding GPC. Consequently, the framework enables exploiting existing results for GPCs to produce converse proofs for their wiretap analogs. The analogy readily extends to multiuser broadcasting scenarios, encompassing broadcast channels (BCs) with deterministic components, degradation ordering between users, and BCs with cooperative receivers. Given a wiretap BC (WTBC) with two receivers and one eavesdropper, an analogous Gelfand-Pinsker BC (GPBC) is constructed by converting the eavesdropper’s observation sequence into a state sequence with an appropriate product distribution (induced by the stealth-wiretap code for the WTBC), and non-causally revealing the states to the encoder. The transition matrix of the state-dependent GPBC is extracted from WTBC’s transition law, with the eavesdropper’s output playing the role of the channel state. Past capacity results for the semi-deterministic (SD) GPBC and the physically-degraded (PD) GPBC with an informed receiver are leveraged to furnish analogy-based converse proofs for the analogous WTBC setups. This characterizes the secrecy-capacity regions of the SD-WTBC and the PD-WTBC, in which the stronger receiver also observes the eavesdropper’s channel output. These derivations exemplify how the wiretap-GP analogy enables translating results on one problem into advances in the study of the other. [ABSTRACT FROM AUTHOR]

We establish the deterministic-code capacity region of a network with one transmitter and two receivers: an ordinary receiver and a robust receiver. The channel to the ordinary receiver is a given (known) discrete memoryless channel, whereas the channel to the robust receiver is an arbitrarily varying channel. Both receivers are required to decode the common message (the better-protected message), whereas only the ordinary receiver is required to decode the private message (the less-protected message). As in the single-user case, under the appropriate compactness and convexity conditions, the capacity region is either empty or else the intersection of the capacity regions of the broadcast channels that the various states induce. [ABSTRACT FROM AUTHOR]

We study two-receiver Poisson channels using tools derived from stochastic calculus. We obtain a general formula for the mutual information over the Poisson channel that allows for conditioning and the use of auxiliary random variables. We then use this formula to compute necessary and sufficient conditions under which one Poisson channel is less noisy and/or more capable than another, which turn out to be distinct from the conditions under which this ordering holds for the discretized versions of the channels. We also use a general formula to determine the capacity region of the more capable Poisson broadcast channel with independent message sets, the more capable Poisson wiretap channel, and the general two-decoder Poisson broadcast channel with degraded message sets. [ABSTRACT FROM AUTHOR]

We consider network coding for a noiseless broadcast channel, where each receiver demands a subset of the messages available at the transmitter and is equipped with noisy side information in the form of an erroneous version of the message symbols it demands. We view the message symbols as elements from a finite field and assume that the number of symbol errors in the noisy side information is upper bounded by a known constant. This communication problem, which we refer to as broadcasting with noisy side information (BNSI), has applications in the re-transmission phase of downlink networks. We derive a necessary and sufficient condition for a linear coding scheme to satisfy the demands of all the receivers in a given BNSI network, and show that syndrome decoding can be used at the receivers to decode the demanded messages from the received codeword and the available noisy side information. We represent BNSI problems as bipartite graphs, and using this representation, classify the family of problems, where linear coding provides bandwidth savings compared to uncoded transmission. We provide a simple algorithm to determine if a given BNSI network belongs to this family of problems, i.e., to identify if linear coding provides an advantage over uncoded transmission for the given BNSI problem. We provide lower bounds and upper bounds on the optimal codelength and constructions of linear coding schemes based on linear error correcting codes. For any given BNSI problem, we construct an equivalent index coding problem. A linear code is a valid scheme for a BNSI problem if and only if it is valid for the constructed scalar linear index coding problem. [ABSTRACT FROM AUTHOR]

A visible light communication broadcast channel is considered, in which a transmitter luminaire communicates with two legitimate receivers in the presence of an external eavesdropper. A number of trusted cooperative half-duplex relay luminaires are deployed to aid with securing the transmitted data. Transmitters are equipped with single light fixtures, containing multiple light emitting diodes, and receiving nodes are equipped with single photo-detectors, rendering the considered setting as a single-input single-output system. Transmission is amplitude-constrained to maintain operation within the light emitting diodes’ dynamic range. Achievable secrecy rate regions are derived under such amplitude constraints for this multi-receiver wiretap channel, first for direct transmission without the relays, and then for multiple relaying schemes: cooperative jamming, decode-and-forward, and amplify-and-forward. Superposition coding with uniform signaling is used at the transmitter and the relays. Further, for each relaying scheme, secure beamforming vectors are carefully designed at the relay nodes in order to hurt the eavesdropper and/or benefit the legitimate receivers. Superiority of the proposed relaying schemes, with secure beamforming, is shown over direct transmission. It is also shown that the best relaying scheme depends on how far the eavesdropper is located from the transmitter and the relays, the number of relays, and their geometric layout. [ABSTRACT FROM AUTHOR]

We derive an achievable rate region (ARR) of the zero-forcing precoder in a 2 $\times $ 2 multi-user multiple-input single-output broadcast intensity-modulation/direct-detection channel. A per-light emitting diode (LED) peak optical power constraint along with a per-LED average optical power constraint with inequality (Type-I constraint) generally considered in optical wireless communication systems is imposed for which we analytically characterize the boundary of the proposed ARR. Then, we compare this ARR with that under a per-LED peak optical power constraint along with a per-LED average power constraint with equality (Type-II constraint), which is considered in visible light communication systems for constant illumination requirement. Our analysis reveals that when the ratio ($\beta $) of the maximum allowed per-LED average optical transmit power to the per-LED peak power is less than or equal to half ($\beta \leq 1/2$), the ARR under both the constraints is the same. However, Type-I constrained system is analytically shown to be more power efficient in terms of the required total average transmit optical power. When $\beta > 1/2$ , the ARR under the Type-I constraint remains constant with increasing $\beta $ , whereas the ARR under the Type-II constraint shrinks. [ABSTRACT FROM AUTHOR]

Multicasting $K$ independent messages via multiple-input multiple-output channels to multiple users where each user already has a subset of messages as side information is studied. A general framework of constructing layered space-time index coding (LSTIC) from a large class of space-time block codes (STBC), including perfect STBC, is proposed. We analyze the proposed LSTIC and show that it provides minimum determinant gains that are exponential with the amount of information contained in the side information for any possible side information. When constructed over a perfect STBC, the proposed LSTIC is itself a perfect STBC and hence many desired properties are preserved. To illustrate, we construct LSTIC over the following well-known STBCs: Golden code; $3\times 3$ , $4\times 4$ , and $6\times 6$ perfect STBCs; and Alamouti code. Simulation results show that the obtained side information gain can be well predicted by our analysis. [ABSTRACT FROM AUTHOR]

Emergence of ultradense networks in 5G communications, Internet of things, and eHealth devices prompts us to develop new communication techniques that can support a large number of low data rate devices. In particular, it has been shown that when the data are real-valued and the observation is complex-valued, widely linear (WL) estimation can be employed in lieu of linear estimation to improve the performance. With these motivations, we study user selection and transmit precoding in multiuser communication systems assuming transmitted signals are one-dimensionally modulated. A closed-form solution for widely linear maximum signal-to-leakage-and-noise ratio precoding is obtained. We also investigate the design of WL maximum ratio transmission, WL zero-forcing, and WL minimum mean square error precoding techniques. Furthermore, to enable an increased number of communication devices, a user selection algorithm compatible with widely linear processing of one-dimensionally modulated signals is proposed. The proposed user selection algorithm can potentially double the number of simultaneously selected users compared to that of conventional user selection methods. [ABSTRACT FROM AUTHOR]

We investigate the maximum coding rate achievable on a two-user broadcast channel for the case where a common message is transmitted with feedback using either fixed-blocklength codes or variable-length codes. For the fixed-blocklength-code setup, we establish nonasymptotic converse and achievability bounds. An asymptotic analysis of these bounds reveals that feedback improves the second-order term compared to the no-feedback case. In particular, for a certain class of antisymmetric broadcast channels, we show that the dispersion is halved. For the variable-length-code setup, we demonstrate that the channel dispersion is zero. [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]

For a wide class of multiuser systems, a subset of capacity region which includes the corner points and the sum—capacity facet has a special structure known as polymatroid. Multiple-access channels with fixed input distributions and multiple-antenna broadcast channels are examples of such systems. Any interior point of the sum—capacity facet can be achieved by time-sharing among corner points or by an alternative method known as rate-splitting. The main purpose of this paper is to find a point on the sum—capacity facet which satisfies a notion of fairness among the active users. This problem is addressed in two cases: i) where the complexity of achieving interior points is not feasible, and ii) where the complexity of achieving interior points is feasible. For the first case, the corner point for which the minimum rate of the active users is maximized is desired. A simple greedy algorithm is introduced to find such an optimum corner point. In addition, it is shown for single-antenna Gaussian multiple-access channels, the resulting corner point is leximin maximal with respect to the set of the corner points. For the second case, the properties of the unique leximin maximal rate vector with respect to the polymatroid are reviewed. It is shown that the problems of deriving the time-sharing coefficients or rate-splitting scheme to attain the leximin maximal vector can be solved by decomposing the problem into some lower dimensional subproblems. In addition, a fast algorithm to compute the time-sharing coefficients to attain a general point on the sum—capacity facet is presented. [ABSTRACT FROM AUTHOR]

Real-world experiments in computer networks typically result in a set of log files, one for each system involved in the experiment. Each log file contains event timestamps based on the local clock of the respective system. These clocks are not perfectly accurate, and deviate from each other. For a thorough analysis, however, a common time basis is necessary. In this paper, we tackle the fundamental problem of creating such a common time base for experiments in networks with local broadcast media, where transmissions can be received by more than one node. We show how clock deviations and event times can be estimated with very high accuracy, without introducing any additional traffic in the network. The proposed method is applied after the experiment is completed, using just the set of local log files as its input. It leads to a large linear program with a very specific structure. We exploit the structure to solve the synchronization problem quickly and efficiently, and present an implementation of a specialized solver. Furthermore, we give analytical and numerical evaluation results and present real-world experiments, all underlining the performance and accuracy of the method. [ABSTRACT FROM AUTHOR]

The H.264 video coding standard achieves significantly improved video compression efficiency and finds important applications in digital video broadcast. To enable H.264 video encoding for digital TV broadcast and maximize its broadcast efficiency, there are two important issues that need to be adequately addressed. First, we need to understand the complex coding mechanism of an H.264 video encoder and develop a model to analyze and control its rate-distortion (R-D) behavior in an accurate and robust manner. Second, the R-D behaviors of individual channels in the broadcast system should be jointly controlled and optimized under bandwidth and buffer constraints so as to maximize the overall broadcast quality. In this paper, we develop a linear rate model and a linear rate control scheme for H.264 video coding. We develop an optimum statistical multiplexing system to allocate bits across video programs (each being encoded by an H.264 encoder) and video frames so that the overall video broadcast quality is maximized. We study the bandwidth and buffer constraints in video broadcast and formulate the optimum statistical multiplexing into a constrained mathematical optimization problem. Realizing that it is impossible to find a close-form solution for global optima, we propose a simple yet efficient algorithm to find a near-optimum solution for joint rate allocation under buffer constraints. Our extensive simulation results demonstrate that the proposed statistical multiplexing system achieves about 40-50% saving in bandwidth, provides a smooth video quality change across programs and frames, and maintains robust decoder buffer control. [ABSTRACT FROM PUBLISHER]

This paper considers broadcast channels with L antennas at the base station and m single-antenna users, where L and m are typically of the same order. We assume that only partial channel state information is available at the base station through a finite rate feedback. Our key observation is that the optimal number of on-users (users turned on), say s, is a function of signal-to-noise ratio (SNR) and feedback rate. In support of this, an asymptotic analysis is employed where L, m and the feedback rate approach infinity linearly. We derive the asymptotic optimal feedback strategy as well as a realistic criterion to decide which users should be turned on. The corresponding asymptotic throughput per antenna, which we define as the spatial efficiency, turns out to be a function of the number of on-users s, and therefore s must he chosen appropriately. Based on the asymptotics, a scheme is developed for systems with finite many antennas and users. Compared with other studies in which s is presumed constant, our scheme achieves a significant gain. Furthermore, our analysis and scheme are valid for heterogeneous systems where different users may have different path loss coefficients and feedback rates. [ABSTRACT FROM AUTHOR]

In this paper, we consider the communication problem that involves transmission of correlated sources over broadcast channels. We consider a graph-based framework for this information transmission problem. The system involves a source coding module and a channel coding module. In the source coding module, the sources are efficiently mapped into a nearly semi-regular bipartite graph, and in the channel coding module, the edges of this graph are reliably transmitted over a broadcast channel. We consider nearly semi-regular bipartite graphs as discrete interface between source coding and channel coding in this multiterminal setting. 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 broadcast 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 broadcast channel. [ABSTRACT FROM AUTHOR]

We study information-theoretic security for discrete memoryless interference and broadcast channels with independent confidential messages sent to two receivers. Confidential messages are transmitted to their respective receivers while ensuring mutual information-theoretic secrecy. That is, each receiver is kept in total ignorance with respect to the message intended for the other receiver. The secrecy level is measured by the equivocation rate at the eavesdropping receiver. In this paper, we present inner and outer bounds on secrecy capacity regions for these two communication systems. The derived outer bounds have an identical mutual information expression that applies to both channel models. The difference is in the input distributions over which the expression is optimized. The inner bound rate regions are achieved by random binning techniques. For the broadcast channel, a double-binning coding scheme allows for both joint encoding and preserving of confidentiality. Furthermore, we show that, for a special case of the interference channel, referred to as the switch channel, derived bounds meet. Finally, we describe several transmission schemes for Gaussian interference channels and derive their achievable rate regions while ensuring mutual information-theoretic secrecy. An encoding scheme in which transmitters dedicate some of their power to create artificial noise is proposed and shown to outperform both time-sharing and simple multiplexed transmission of the confidential messages. [ABSTRACT FROM AUTHOR]

Time-slotted ALOHA packetized multiple-access has been extensively used in satellite communications, and has recently been attracting considerable attention in wireless Ad- hoc networks. In this paper, we consider a time-slotted ALOHA system which combines multiple-access, broadcasting channels and rate splitting. This system allows some transmission bits to be reliably received even when collisions occur and more bits to be reliably received in the absence of collisions. In contrast to previous work, our work focuses on the case in which the transmission channels obey i.i.d (independent and identically distributed) Rayleigh fading. Two fundamental problems are considered. The first one is the calculation of the system capacity, and the second one is how to select an appropriate channel coding scheme with which the system achieves its capacity. We shall review the single time slotted capacity, and present the total capacity expression with the knowledge of channel side information. We will then derive a threshold for the transmission probability in a single time slot provided that all the users have the same transmission probability. It will be shown that when the transmission probability is greater than the derived threshold, low-resolution codes can help the system achieve its capacity. We shall also present an explicit estimation method for computing the threshold, and prove that it can be extended to the more general case when the transmission probabilities are approximately equal. [ABSTRACT FROM PUBLISHER]

This paper focuses on the broadcast channel of an interactive multibeam broadband satellite (MBS) system with a transparent architecture. In particular, a cross-layer design is proposed for the packet scheduling on a forward link that implements adaptive coding and modulation (ACM). A cross-layer approach is considered whereby the physical and medium access control (MAC) layers share knowledge of the channel dynamics in presence of ACM. Transmission power and symbol rate are assumed to be constant, and hence the bit rate is time and space dependant according to the channel conditions. An architecture is proposed which relies on the physical characteristics of the Ka-band satellite propagation channel and the definition of "correlated areas". The stable throughput region has been derived assuming full-queue traffic conditions. Moreover, the proposed architecture is simple but flexible enough to allow the implementation of different scheduling policies like the proportionally fair or opportunistic ones. Finally, a new time-fair policy appropriate for wet seasons is proposed. It has the property of isolating users in clear-sky conditions from the effects of the reduced transmission rate experienced by users under a rain fade [ABSTRACT FROM PUBLISHER]

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]

As different types of wireless networks are converging into an all-IP network, i.e., the Internet, it can be expected that in the near future video-on-demand (VoD) will be widely applied to many interesting services, and users can access these services using heterogeneous terminals via heterogeneous wired/wireless access networks. Many periodic broadcasting protocols have been proposed to reduce the implementation cost of VoD systems. However, most of the protocols assumed homogeneity for user terminals, while in practice, user terminals are usually quite different in their processing power, buffer space, and power. To address this problem, a few periodic broadcasting protocols providing the same video quality for all heterogeneous clients have been proposed recently. In this paper, we proposed a novel heterogeneous VoD broadcasting technique called Catch and Rest (CAR) to accommodate bandwidth heterogeneity without sacrificing user video quality. Then, we provide mathematic analysis to calculate the client bandwidth and buffer space requirements of CAR. Finally, we present our performance evaluation results for CAR. Our results show that under the same system resources (i.e., server and network bandwidth), CAR provides more uniform and acceptable service latency for all heterogeneous clients compared to previous works. [ABSTRACT FROM AUTHOR]

Recently a number of researchers have proposed and investigated new video-on-demand architectures that make use of network multicast to achieve vastly improved efficiency. Techniques such as batching, patching, periodic broadcasting, chaining, and piggybacking have been explored both in isolation and in combinations. This study investigates a new tool in the arsenal-channel folding, where aggressive client-side caching is used to merge clients from one multicast channel into the other. In particular, this channel folding algorithm is applied to a previously proposed unified video-on-demand (UVoD)) architecture to demonstrate and to quantify its impact on the performance and the tradeoff in a multicast video distribution architecture. This paper presents this channel folding algorithm in the context of UVoD) and derives a performance model to obtain the system latency, the near-optimal channel partition policy, and the client buffer requirement. Numerical results show that channel folding can double the capacity of UVoD) with a remarkably small overhead in the client buffer requirement. [ABSTRACT FROM PUBLISHER]

Manly essential multimedia applications rely on video-on-demand technology to deliver a video to different users. A number of periodic broadcast techniques have been proposed for the cost-effective implementation of such systems. Most of these techniques I would either try to minimize the server band- width, user bandwidth, user storage, user access latency to the video, or a combination of some of the aforementioned parameters. On the other hand, the implementation strategies of these broadcast schedules would necessitate a minimum bandwidth requirement for all users. Multi-resolution techniques address the heterogeneity problem by sacrificing user video quality. In this paper, we consider a different approach that does not possess this disadvantage. using an incremental channel design at the server side, and a specific broadcast schedule, users can choose among a range of band widths to use to download the video at the cost of their access latency and not to the video quality. We prove the correctness of the proposed solution; provide mathematical analysis to demonstrate its heterogeneous behavior, and present performance studies to illustrate its efficiency. [ABSTRACT FROM AUTHOR]

For the $K=2$ user MISO BC, i.e., the wireless broadcast channel where a transmitter equipped with $K=2$ antennas sends independent messages to $K=2$ receivers each of which is equipped with a single antenna, the generalized degrees of freedom (GDoFs) region are characterized for arbitrary channel strength and channel uncertainty levels for each of the channel coefficients. The result is extended to K>2 users under additional restrictions which include the assumption of symmetry. [ABSTRACT FROM AUTHOR]

Improved lower bounds are derived on the average and worst case rate-memory tradeoffs of the Maddah-Ali and Niesen-coded caching scenario. For any number of users and files and for arbitrary cache sizes, the multiplicative gap between the exact rate-memory tradeoff and the new lower bound is shown to be less than 2.315 in the worst case scenario and 2.507 in the average-case scenario. [ABSTRACT FROM AUTHOR]

We characterize delay minimal power scheduling policies in energy harvesting communication systems. We consider a continuous-time system, where the delay experienced by each bit is given by the time spent by the bit in the queue waiting to be transmitted to its receiver. We first consider a single-user channel, where the transmitter has a finite-sized battery to save its harvested energy. Data arrives during the course of communication and are saved in a finite data buffer as well. We find the optimal power policy that minimizes the average delay experienced by the bits subject to energy and data causality constraints. We characterize the optimal solution in terms of Lagrange multipliers, and calculate their values in a recursive manner. We show that, different from the existing literature, the optimum transmission power is not constant between the energy and data arrival events; the transmission power starts high, decreases linearly, and potentially reaches zero between energy and data arrivals. Intuitively, untransmitted bits experience cumulative delay due to the bits to be transmitted ahead of them, and hence the reason for transmission power starting high and decreasing over time. Next, we study a multiuser version of this problem, namely, a two-user broadcast channel, and characterize the optimal transmission policies that minimize the sum delay. For this setting, we consider the case, where the transmitter has an infinite-sized battery, and that all data packets intended for the receivers are available at the beginning of the communication session. We characterize the optimal solution in terms of Lagrange multipliers, and present an iterative solution that calculates their values. Our results show that in the optimal policy, both users may not be served simultaneously all the time; there may be times, where only one of the two users is served alone. We also show that the optimal policy may have gaps in transmission in between energy arrivals, where none of the users is served, echoing the results of the single-user setting. [ABSTRACT FROM AUTHOR]

We consider the problem of developing coding techniques and deriving achievable rate regions for discrete memoryless broadcast channels with three receivers (3-DBC). We begin by identifying a novel vector additive 3-DBC for which we characterize an upper bound on the the largest achievable rate region based on unstructured codes, henceforth referred to as \pmb \mathscr U\mathcal M -region. We propose a coding technique based on coset codes that yield an achievable rate triple not contained within \pmb \mathscr U\mathcal M -region. We generalize the proposed coding technique using a new ensemble of codes—partitioned coset codes (PCC)—containing both empirical and algebraic properties, and evaluate its performance to derive an achievable rate region for the general 3-DBC. The new elements in this derivation are binning and joint typicality encoding and decoding of statistically correlated PCCs. We validate the utility of this technique by identifying non-additive instances of 3-DBC for which the proposed coding techniques based on PCC yield strictly larger rates. [ABSTRACT FROM AUTHOR]

The K -receiver degraded broadcast channel with secrecy outside a bounded range is studied, in which a transmitter sends K messages to K receivers, and the channel quality gradually degrades from receiver K to receiver 1. Each receiver k , for 1\leq k\leq K , and to be kept ignorant of W_{k+2},\ldots,W_{K} , for k=1,\ldots, K-2 . Thus, each message Wk is kept secure from receivers with at least two-level worse channel quality, i.e., receivers 1, \ldots , $k-2$ . The secrecy capacity region is fully characterized. The achievable scheme designates one superposition layer to each message with binning employed for each layer. Joint embedded coding and binning are employed to protect all upper-layer messages from lower-layer receivers. Furthermore, the scheme allows adjacent layers to share rates so that part of the rate of each message can be shared with its immediate upper-layer message to enlarge the rate region. More importantly, an induction approach is developed to perform Fourier-Motzkin elimination of 2K$ variables from the order of K^{2} bounds to obtain a close-form achievable rate region. An outer bound is developed that matches the achievable rate region, whose proof involves recursive construction of the rate bounds and exploits the intuition gained from the achievable scheme. [ABSTRACT FROM PUBLISHER]