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Information Theory, IEEE Transactions on

Issue 10 • Date Oct. 2013

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Displaying Results 1 - 25 of 63
  • Table of Contents

    Page(s): C1 - C4
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    Freely Available from IEEE
  • IEEE Transactions on Information Theory publication information

    Page(s): C2
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    Freely Available from IEEE
  • Capacity Region of Cooperative Multiple-Access Channel With States

    Page(s): 6153 - 6174
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (6549 KB) |  | HTML iconHTML  

    We consider a two-user state-dependent multiaccess channel in which the states of the channel are known noncausally to one of the encoders and only strictly causally to the other encoder. Both encoders transmit a common message and, in addition, the encoder that knows the states noncausally transmits an individual message. We find explicit characterizations of the capacity region of this communication model in both discrete memoryless and memoryless Gaussian cases. In particular, the capacity region analysis demonstrates the utility of the knowledge of the states only strictly causally at the encoder that sends only the common message in general. More specifically, in the discrete memoryless setting, we show that such a knowledge is beneficial and increases the capacity region in general. In the Gaussian setting, we show that such a knowledge does not help, and the capacity is same as if the states were completely unknown at the encoder that sends only the common message. Furthermore, we also study the special case in which the two encoders transmit only the common message and show that the knowledge of the states only strictly causally at the encoder that sends only the common message is not beneficial in this case, in both discrete memoryless and memoryless Gaussian settings. The analysis also reveals optimal ways of exploiting the knowledge of the state only strictly causally at the encoder that sends only the common message when such a knowledge is beneficial. The encoders collaborate to convey to the decoder a lossy version of the state, in addition to transmitting the information messages through a generalized Gel'fand-Pinsker binning. Particularly important in this problem are the questions of 1) optimal ways of performing the state compression and 2) whether or not the compression indices should be decoded uniquely. By developing two optimal coding schemes that perform this state compression differently, we show that when used as parts of appropriately tun- d encoding and decoding processes, both compression à-la noisy network coding by Lim or the quantize-map-and-forward by Avestimeher , i.e., with no binning, and compression using Wyner-Ziv binning are optimal. The scheme that uses Wyner-Ziv binning shares elements with Cover and El Gamal original compress-and-forward, but differs from it mainly in that backward decoding is employed instead of forward decoding and the compression indices are not decoded uniquely. Finally, by exploring the properties of our outer bound, we show that, although not required in general, the compression indices can in fact be decoded uniquely essentially without altering the capacity region, but at the expense of larger alphabets sizes for the auxiliary random variables. View full abstract»

    Open Access
  • An Achievable Rate Region for the Broadcast Channel With Feedback

    Page(s): 6175 - 6191
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5914 KB) |  | HTML iconHTML  

    A single-letter achievable rate region is proposed for the two-receiver discrete memoryless broadcast channel with generalized feedback. The coding strategy involves block-Markov superposition coding using Marton's coding scheme for the broadcast channel without feedback as the starting point. If the message rates in the Marton scheme are too high to be decoded at the end of a block, each receiver is left with a list of messages compatible with its output. Resolution information is sent in the following block to enable each receiver to resolve its list. The key observation is that the resolution information of the first receiver is correlated with that of the second. This correlated information is efficiently transmitted via joint source-channel coding, using ideas similar to the Han-Costa coding scheme. Using the result, we obtain an achievable rate region for the stochastically degraded additive white Gaussian noise broadcast channel with noisy feedback from only one receiver. It is shown that this region is strictly larger than the no-feedback capacity region. View full abstract»

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  • Optimal Coding for the Binary Deletion Channel With Small Deletion Probability

    Page(s): 6192 - 6219
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (9595 KB) |  | HTML iconHTML  

    The binary deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability d, and when they are not deleted, they are not affected by the channel. Despite significant effort, little is known about the capacity of this channel and even less about optimal coding schemes. In this paper, we develop a new systematic approach to this problem, by demonstrating that capacity can be computed in a series expansion for small deletion probability. We compute three leading terms of this expansion, and find an input distribution that achieves capacity up to this order. This constitutes the first optimal random coding result for the deletion channel. The key idea employed is the following: We understand perfectly the deletion channel with deletion probability d=0. It has capacity 1 and the optimal input distribution is iid Bernoulli (1/2). It is natural to expect that the channel with small deletion probabilities has a capacity that varies smoothly with d, and that the optimal input distribution is obtained by smoothly perturbing the iid Bernoulli (1/2) process. Our results show that this is indeed the case. View full abstract»

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  • Universal Estimation of Directed Information

    Page(s): 6220 - 6242
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    Four estimators of the directed information rate between a pair of jointly stationary ergodic finite-alphabet processes are proposed, based on universal probability assignments. The first one is a Shannon-McMillan-Breiman-type estimator, similar to those used by Verdú in 2005 and Cai in 2006 for estimation of other information measures. We show the almost sure and L1 convergence properties of the estimator for any underlying universal probability assignment. The other three estimators map universal probability assignments to different functionals, each exhibiting relative merits such as smoothness, nonnegativity, and boundedness. We establish the consistency of these estimators in almost sure and L1 senses, and derive near-optimal rates of convergence in the minimax sense under mild conditions. These estimators carry over directly to estimating other information measures of stationary ergodic finite-alphabet processes, such as entropy rate and mutual information rate, with near-optimal performance and provide alternatives to classical approaches in the existing literature. Guided by these theoretical results, the proposed estimators are implemented using the context-tree weighting algorithm as the universal probability assignment. Experiments on synthetic and real data are presented, demonstrating the potential of the proposed schemes in practice and the utility of directed information estimation in detecting and measuring causal influence and delay. View full abstract»

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  • Feedback Communication and Control Over a Single Channel

    Page(s): 6243 - 6257
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    This paper explores the problem of feedback coding for a channel whose output is simultaneously used for two purposes: it is decoded to establish reliable communication, and it is used to control a dynamical system. In general, there is a tradeoff between the rate of communication and the accuracy of control. An intuitive communication and control strategy is analyzed and shown to be optimal in several cases of interest. Using methods from stochastic control, a corresponding upper bound is derived on the rate for a given cost, and this bound can be applied to find the capacity for an interesting class of channels. Under certain regularity conditions, the capacity has a simple characterization, and a series of examples is provided to demonstrate how it can be calculated. View full abstract»

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  • A Constrained Coding Approach to Error-Free Half-Duplex Relay Networks

    Page(s): 6258 - 6260
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    We show that the broadcast capacity of an infinite-depth tree-structured network of error-free half-duplex-constrained relays can be achieved using constrained coding at the source and symbol forwarding at the relays. View full abstract»

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  • Likelihood Ratios and Inference for Poisson Channels

    Page(s): 6261 - 6272
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3076 KB) |  | HTML iconHTML  

    In recent years, infinite-dimensional methods have been introduced for Gaussian channel estimation. The aim of this paper is to study the application of similar methods to Poisson channels. In particular, we compute the noncausal conditional mean estimator of a Poisson channel using the likelihood ratio and the discrete Malliavin gradient. This algorithm is suitable for numerical implementation via the Monte-Carlo scheme. As an application, we provide a new proof of a very deep and remarkable formula in Information Theory obtained recently in the literature and relating the derivatives of the input-output mutual information of a general Poisson channel and the conditional mean estimator of the input regardless the distribution of the latter. The use of the aforementioned stochastic analysis techniques allows us to extend these results to more general channels such as mixed Gaussian-Poisson channels. View full abstract»

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  • Information Theory of DNA Shotgun Sequencing

    Page(s): 6273 - 6289
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3457 KB) |  | HTML iconHTML  

    DNA sequencing is the basic workhorse of modern day biology and medicine. Shotgun sequencing is the dominant technique used: many randomly located short fragments called reads are extracted from the DNA sequence, and these reads are assembled to reconstruct the original sequence. A basic question is: given a sequencing technology and the statistics of the DNA sequence, what is the minimum number of reads required for reliable reconstruction? This number provides a fundamental limit to the performance of any assembly algorithm. For a simple statistical model of the DNA sequence and the read process, we show that the answer admits a critical phenomenon in the asymptotic limit of long DNA sequences: if the read length is below a threshold, reconstruction is impossible no matter how many reads are observed, and if the read length is above the threshold, having enough reads to cover the DNA sequence is sufficient to reconstruct. The threshold is computed in terms of the Renyi entropy rate of the DNA sequence. We also study the impact of noise in the read process on the performance. View full abstract»

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  • Parallel Opportunistic Routing in Wireless Networks

    Page(s): 6290 - 6300
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2491 KB) |  | HTML iconHTML  

    We study benefits of opportunistic routing in a large wireless ad hoc network by examining how the power, delay, and total throughput scale as the number of source-destination pairs increases up to the operating maximum. Our opportunistic routing is novel in a sense that it is massively parallel, i.e., it is performed by many nodes simultaneously to maximize the opportunistic gain while controlling the interuser interference. The scaling behavior of conventional multihop transmission that does not employ opportunistic routing is also examined for comparison. Our main results indicate that our opportunistic routing can exhibit a net improvement in overall power-delay tradeoff over the conventional routing by providing up to a logarithmic boost in the scaling law. Such a gain is possible since the receivers can tolerate more interference due to the increased received signal power provided by the multi user diversity gain, which means that having more simultaneous transmissions is possible. View full abstract»

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  • Markov Approximation for Combinatorial Network Optimization

    Page(s): 6301 - 6327
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (7399 KB) |  | HTML iconHTML  

    Many important network design problems are fundamentally combinatorial optimization problems. A large number of such problems, however, cannot readily be tackled by distributed algorithms. The Markov approximation framework studied in this paper is a general technique for synthesizing distributed algorithms. We show that when using the log-sum-exp function to approximate the optimal value of any combinatorial problem, we end up with a solution that can be interpreted as the stationary probability distribution of a class of time-reversible Markov chains. Selected Markov chains among this class yield distributed algorithms that solve the log-sum-exp approximated combinatorial network optimization problem. By examining three applications, we illustrate that the Markov approximation technique not only provides fresh perspectives to existing distributed solutions, but also provides clues leading to the construction of new distributed algorithms in various domains with provable performance. We believe the Markov approximation techniques will find applications in many other network optimization problems. View full abstract»

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  • Throughput-Delay Analysis of Random Linear Network Coding for Wireless Broadcasting

    Page(s): 6328 - 6341
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3275 KB) |  | HTML iconHTML  

    In an unreliable single-hop broadcast network setting, we investigate the throughput and decoding-delay performance of random linear network coding as a function of the coding window size and the network size. Our model consists of a source transmitting packets of a single flow to a set of n users over independent time-correlated erasure channels. The source performs random linear network coding (RLNC) over k (coding window size) packets and broadcasts them to the users. We note that the broadcast throughput of RLNC must vanish with increasing n, for any fixed k. Hence, in contrast to other works in the literature, we investigate how the coding window size k must scale for increasing n. Our analysis reveals that the coding window size of Θ(ln(n)) represents a phase transition rate, below which the throughput converges to zero, and above which, it converges to the broadcast capacity. Further, we characterize the asymptotic distribution of decoding delay and provide approximate expressions for the mean and variance of decoding delay for the scaling regime of k=ω(ln(n)). These asymptotic expressions reveal the impact of channel correlations on the throughput and delay performance of RLNC. We also show that how our analysis can be extended to other rateless block coding schemes such as the LT codes. Finally, we comment on the extension of our results to the cases of dependent channels across users and asymmetric channel model. View full abstract»

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  • Modular Methodology for the Network Calculus in a Time-Varying Context

    Page(s): 6342 - 6356
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3940 KB) |  | HTML iconHTML  

    Network calculus (NC) is a set of rules and results for computing bounds for performance parameters of communication systems, such as end-to-end delay, maximum backlog, and service curves. Previous works show that the problem of determining performance bounds of communication networks is simplified if modeled using the dioid algebra. In this paper, we propose a methodology that allows the treatment of NC problems in a modular basis in a time-varying context, i.e., when curves vary with time. From the proposed methodology, we extend some results of the literature and derive new results on NC. Among the obtained results, we introduce an alternative representation of service guarantees that better explore the available knowledge of systems. We also define variable delay functions that lead to less conservative delay bounds than those in the literature. Finally, we analyze a FIFO multiplexer with M input flows. View full abstract»

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  • On the Stability of Finite Queue Slotted Aloha Protocol

    Page(s): 6357 - 6366
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2294 KB) |  | HTML iconHTML  

    We revisit the stability analysis of the well-known slotted Aloha protocol with a finite number of queues. Under standard modeling assumptions, we derive a sufficient condition for the stability by applying a positive recurrence criterion due to Rosberg (JAP, vol. 17, no. 3, 1980). Our sufficiency condition for stability is linear in arrival rates and does not require knowledge of the stationary joint statistics of queue lengths as has been the case in previous results. We also derive some sufficient conditions for instability of the protocol. We believe that the technique reported here could be useful in analyzing other stability problems in countable space Markovian settings. View full abstract»

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  • On the Queue-Overflow Probability of Wireless Systems: A New Approach Combining Large Deviations With Lyapunov Functions

    Page(s): 6367 - 6392
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (7186 KB) |  | HTML iconHTML  

    In this paper, we study the queue-overflow probability of wireless scheduling algorithms. In wireless networks operated under queue-length-based scheduling algorithms, there often exists a tight coupling between the service-rate process, the system backlog process, the arrival process, and the stochastic process governing channel variations. Although one can use sample-path large-deviation techniques to form an estimate of the queue-overflow probability, the formulation leads to a difficult multidimensional calculus-of-variations problem. In this paper, we present a new technique to address this complexity issue. Using ideas from the Lyapunov function approach in control theory, this technique maps the complex multidimensional calculus-of-variations problem to a 1-D calculus-of-variations problem, and the latter is often much easier to solve. Further, under appropriate conditions, we show that when a scheduling algorithm minimizes the drift of a Lyapunov function at each point of every fluid sample path, the algorithm will be optimal in the sense that it maximizes the asymptotic decay rate of the probability that the Lyapunov function value exceeds a given threshold. We believe that these results can potentially be used to study the queue-overflow probability of a large class of wireless scheduling algorithms and to design new scheduling algorithms with optimal overflow probabilities. View full abstract»

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  • The Impact of Queue Length Information on Buffer Overflow in Parallel Queues

    Page(s): 6393 - 6404
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    We consider a system consisting of N parallel queues, served by one server. Time is slotted, and the server serves one of the queues in each time slot, according to some scheduling policy. We first characterize the exponent of the buffer overflow probability and the most likely overflow trajectories under the Longest Queue First (LQF) scheduling policy. Under statistically identical arrivals to each queue, we show that the buffer overflow exponents can be simply expressed in terms of the total system occupancy exponent of m parallel queues, for some m ≤ N. We next turn our attention to the rate of queue length information needed to operate a scheduling policy, and its relationship to the buffer overflow exponents. It is known that queue length blind policies such as processor sharing and random scheduling perform worse than the queue aware LQF policy, when it comes to buffer overflow probability. However, we show that the overflow exponent of the LQF policy can be preserved with arbitrarily infrequent queue length updates. View full abstract»

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  • Capacity of a Class of Linear Binary Field Multisource Relay Networks

    Page(s): 6405 - 6420
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4982 KB) |  | HTML iconHTML  

    In this paper, we study a layered linear binary field network with time-varying channels, which is a simplified model reflecting broadcast, interference, and fading natures of wireless communications. We observe that fading can play an important role in mitigating interuser interference effectively for both single-hop and multihop networks. We propose new coding schemes with randomized ergodic channel pairing, which exploit such channel variations, and derive their achievable ergodic rates. By comparing them with the cut-set upper bound, the capacity region of single-hop networks and the sum capacity of multihop networks are characterized for some classes of channel distributions and network topologies. View full abstract»

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  • Multiple-Input Multiple-Output Two-Way Relaying: A Space-Division Approach

    Page(s): 6421 - 6440
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5024 KB) |  | HTML iconHTML  

    We propose a novel space-division-based network-coding scheme for multiple-input multiple-output (MIMO) two-way relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed scheme, the overall signal space at the relay is divided into two subspaces. In one subspace, the spatial streams of the two users have nearly orthogonal directions and are completely decoded at the relay. In the other subspace, the signal directions of the two users are nearly parallel, and linear functions of the spatial streams are computed at the relay, following the principle of physical-layer network coding. Based on the recovered messages and message-functions, the relay generates and forwards network-coded messages to the two users. We show that, at high signal-to-noise ratio, the proposed scheme achieves the asymptotic sum-rate capacity of the MIMO TWRC within [ 1/ 2]log(5/4) ≈ 0.161 bits per user-antenna, for any antenna configuration and any channel realization. We perform large-system analysis to derive the average sum-rate of the proposed scheme over Rayleigh-fading MIMO TWRCs. We show that the average asymptotic sum-rate gap to the capacity is at most 0.053 bits per relay-antenna. It is demonstrated that the proposed scheme significantly outperforms the existing schemes. View full abstract»

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  • Joint Spatial Division and Multiplexing—The Large-Scale Array Regime

    Page(s): 6441 - 6463
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6169 KB) |  | HTML iconHTML  

    We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing (FDD) systems, for which uplink/downlink channel reciprocity cannot be exploited. In the proposed scheme, the multiuser MIMO downlink precoder is obtained by concatenating a prebeamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional “effective” channel matrix. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is approached in the large number of antennas limit. For this case, we use Szego's asymptotic theory of Toeplitz matrices to show that a DFT-based prebeamforming matrix is near-optimal, requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a 2-D base station antenna array, with 3-D beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the prebeamforming optimization and calculate the system spectral efficiency under proportional fairness and max-min fairness criteria, showing extremely attractive performance. Our numerical results are obtained via asymptotic random matrix theory, avoiding lengthy Monte Carlo simulations and providing accurate results for realistic (finite) number of antennas and users. View full abstract»

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  • Statistical Beamforming on the Grassmann Manifold for the Two-User Broadcast Channel

    Page(s): 6464 - 6489
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    A Rayleigh fading spatially correlated broadcast setting with M = 2 antennas at the transmitter and two users (each with a single antenna) is considered. It is assumed that the users have perfect channel information about their links, whereas the transmitter has only statistical information of each user's link (covariance matrix of the vector channel). A low-complexity linear beamforming strategy that allocates equal power and one spatial eigenmode to each user is employed at the transmitter. Beamforming vectors on the Grassmann manifold that depend only on statistical information are to be designed at the transmitter to maximize the ergodic sum-rate delivered to the two users. Toward this goal, the beamforming vectors are first fixed and a closed-form expression is obtained for the ergodic sum-rate in terms of the covariance matrices of the links. This expression is nonconvex in the beamforming vectors ensuring that the classical Lagrange multiplier technique is not applicable. Despite this difficulty, the optimal solution to this problem is shown to be the same as the solution to the maximization of an appropriately defined average signal-to-interference and noise ratio metric for each user. This solution is the dominant generalized eigenvector of a pair of positive-definite matrices where the first matrix is the covariance matrix of the forward link and the second is an appropriately designed “effective” interference covariance matrix. In this sense, our work is a generalization of optimal signalling along the dominant eigenmode of the transmit covariance matrix in the single-user case. Finally, the ergodic sum-rate for the general broadcast setting with M antennas at the transmitter and M-users (each with a single antenna) is obtained in terms of the covariance matrices of the links and the beamforming vectors. View full abstract»

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  • SINR Statistics of Correlated MIMO Linear Receivers

    Page(s): 6490 - 6500
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2767 KB) |  | HTML iconHTML  

    Linear receivers offer a low complexity option for multiantenna communication systems. Therefore, understanding the outage behavior of the corresponding SINR is important in a fading mobile environment. In this paper, we introduce a large deviation method, valid nominally for a large number M of antennas, which provides the probability density of the SINR of Gaussian channel MIMO minimum mean square error (MMSE) and zero-forcing (ZF) receivers, with arbitrary transmission power profiles and in the presence of receiver antenna correlations. This approach extends the Gaussian approximation of the SINR, valid for large M asymptotically close to the center of the distribution, to obtain the non-Gaussian tails of the distribution. Our methodology allows us to calculate the SINR distribution to next-to-leading order ( O(1/M)) and showcase the deviations from approximations that have appeared in the literature (e.g., the Gaussian or the generalized Gamma distribution). We also analytically evaluate the outage probability, as well as the uncoded bit-error-rate. We find that our approximation is quite accurate even for the smallest antenna arrays (2 × 2). View full abstract»

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  • On Convexity of Error Rates in Digital Communications

    Page(s): 6501 - 6516
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    Convexity properties of error rates of a class of decoders, including the maximum-likelihood/min-distance one as a special case, are studied for arbitrary constellations, bit mapping, and coding. Earlier results obtained for the additive white Gaussian noise channel are extended to a wide class of noise densities, including unimodal and spherically invariant noise. Under these broad conditions, symbol and bit error rates are shown to be convex functions of the signal-to-noise ratio (SNR) in the high-SNR regime with an explicitly determined threshold, which depends only on the constellation dimensionality and minimum distance, thus enabling an application of the powerful tools of convex optimization to such digital communication systems in a rigorous way. It is the decreasing nature of the noise power density around the decision region boundaries that ensures the convexity of symbol error rates in the general case. The known high/low-SNR bounds of the convexity/concavity regions are tightened and no further improvement is shown to be possible in general. The high-SNR bound fits closely into the channel coding theorem: all codes, including capacity-achieving ones, whose decision regions include the hardened noise spheres (from the noise sphere hardening argument in the channel coding theorem), satisfy this high-SNR requirement and thus has convex error rates in both SNR and noise power. We conjecture that all capacity-achieving codes have convex error rates. Convexity properties in signal amplitude and noise power are also investigated. Some applications of the results are discussed. In particular, it is shown that fading is convexity-preserving and is never good in low dimensions under spherically invariant noise, which may also include any linear diversity combining. View full abstract»

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  • On an Achievable Rate of Large Rayleigh Block-Fading MIMO Channels With No CSI

    Page(s): 6517 - 6541
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    Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The achievable rates of successive decoding (SD) receivers based on the linear minimum mean-squared error (LMMSE) channel estimation are analyzed in the large-system limit, by using the replica method under the assumption of replica symmetry. It is shown that negligible pilot information is best in terms of the achievable rates of the SD receivers in the large-system limit. The obtained analytical formulas of the achievable rates can improve the existing lower bound on the capacity of the MIMO channel with no channel state information (CSI), derived by Hassibi and Hochwald, for all SNRs. The comparison between the obtained bound and a high-SNR approximation of the channel capacity, derived by Zheng and Tse, implies that the high-SNR approximation is unreliable unless quite high SNR is considered. Energy efficiency in the low-SNR regime is also investigated in terms of the power per information bit required for reliable communication. The required minimum power is shown to be achieved at a positive rate for the SD receiver with no CSI, whereas it is achieved in the zero-rate limit for the case of perfect CSI available at the receiver. Moreover, numerical simulations imply that the presented large-system analysis can provide a good approximation for not so large systems. The results in this paper imply that SD schemes can provide a significant performance gain in the low-to-moderate SNR regimes, compared to conventional receivers based on one-shot channel estimation. View full abstract»

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  • On the Degrees of Freedom of K-User SISO Interference and X Channels With Delayed CSIT

    Page(s): 6542 - 6561
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    The K-user single-input single-output (SISO) additive white Gaussian noise (AWGN) interference channel and 2×K SISO AWGN X channel are considered, where the transmitters have delayed channel state information (CSI) through noiseless feedback links. Multiphase transmission schemes are proposed for both channels which possess novel ingredients, namely, multiphase partial interference nulling, distributed interference management via user scheduling, and distributed higher order symbol generation. The achieved degree-of-freedom (DoF) values are greater than the best previously known DoFs for both channels with delayed CSI at the transmitters. View full abstract»

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IEEE Transactions on Information Theory publishes papers concerned with the transmission, processing, and utilization of information.

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Editor-in-Chief
Frank R. Kschischang

Department of Electrical and Computer Engineering