On the Throughput of Channels that Wear Out

This work investigates the fundamental limits of communication over a noisy discrete memoryless channel that wears out, in the sense of signal-dependent catastrophic failure. In particular, we consider a channel that starts as a memoryless binary-input channel and when the number of transmitted ones causes a sufficient amount of damage, the channel ceases to convey signals. Constant composition codes are adopted to obtain an achievability bound and the left-concave right-convex inequality is then refined to obtain a converse bound on the log-volume throughput for channels that wear out. Since infinite blocklength codes will always wear out the channel for any finite threshold of failure and therefore cannot convey information at positive rates, we analyze the performance of finite blocklength codes to determine the maximum expected transmission volume at a given level of average error probability. We show that this maximization problem has a recursive form and can be solved by dynamic programming. Numerical results demonstrate that a sequence of block codes is preferred to a single block code for streaming sources.Comment: 23 pages, 1 table, 11 figures, submitted to IEEE Transactions on Communication

Multiuser Switched Diversity Scheduling Schemes

Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions.Comment: Accepted at IEEE Transactions on Communications, to appear 2012, funded by NPRP grant 08-577-2-241 from QNR

Throughput Scaling of Wireless Networks With Random Connections

This work studies the throughput scaling laws of ad hoc wireless networks in the limit of a large number of nodes. A random connections model is assumed in which the channel connections between the nodes are drawn independently from a common distribution. Transmitting nodes are subject to an on-off strategy, and receiving nodes employ conventional single-user decoding. The following results are proven: 1) For a class of connection models with finite mean and variance, the throughput scaling is upper-bounded by $O(n^{1/3})$ for single-hop schemes, and $O(n^{1/2})$ for two-hop (and multihop) schemes. 2) The $\Theta (n^{1/2})$ throughput scaling is achievable for a specific connection model by a two-hop opportunistic relaying scheme, which employs full, but only local channel state information (CSI) at the receivers, and partial CSI at the transmitters. 3) By relaxing the constraints of finite mean and variance of the connection model, linear throughput scaling $\Theta (n)$ is achievable with Pareto-type fading models.Comment: 13 pages, 4 figures, To appear in IEEE Transactions on Information Theor

Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities

This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error probabilities for various problems are bounded above by a non-vanishing constant and the spotlight is shone on achievable coding rates as functions of the growing blocklengths. This represents the study of asymptotic estimates with non-vanishing error probabilities. In Part I, after reviewing the fundamentals of information theory, we discuss Strassen's seminal result for binary hypothesis testing where the type-I error probability is non-vanishing and the rate of decay of the type-II error probability with growing number of independent observations is characterized. In Part II, we use this basic hypothesis testing result to develop second- and sometimes, even third-order asymptotic expansions for point-to-point communication. Finally in Part III, we consider network information theory problems for which the second-order asymptotics are known. These problems include some classes of channels with random state, the multiple-encoder distributed lossless source coding (Slepian-Wolf) problem and special cases of the Gaussian interference and multiple-access channels. Finally, we discuss avenues for further research.Comment: Further comments welcom

Multiuser Scheduling in a Markov-modeled Downlink using Randomly Delayed ARQ Feedback

We focus on the downlink of a cellular system, which corresponds to the bulk of the data transfer in such wireless systems. We address the problem of opportunistic multiuser scheduling under imperfect channel state information, by exploiting the memory inherent in the channel. In our setting, the channel between the base station and each user is modeled by a two-state Markov chain and the scheduled user sends back an ARQ feedback signal that arrives at the scheduler with a random delay that is i.i.d across users and time. The scheduler indirectly estimates the channel via accumulated delayed-ARQ feedback and uses this information to make scheduling decisions. We formulate a throughput maximization problem as a partially observable Markov decision process (POMDP). For the case of two users in the system, we show that a greedy policy is sum throughput optimal for any distribution on the ARQ feedback delay. For the case of more than two users, we prove that the greedy policy is suboptimal and demonstrate, via numerical studies, that it has near optimal performance. We show that the greedy policy can be implemented by a simple algorithm that does not require the statistics of the underlying Markov channel or the ARQ feedback delay, thus making it robust against errors in system parameter estimation. Establishing an equivalence between the two-user system and a genie-aided system, we obtain a simple closed form expression for the sum capacity of the Markov-modeled downlink. We further derive inner and outer bounds on the capacity region of the Markov-modeled downlink and tighten these bounds for special cases of the system parameters.Comment: Contains 22 pages, 6 figures and 8 tables; revised version including additional analytical and numerical results; work submitted, Feb 2010, to IEEE Transactions on Information Theory, revised April 2011; authors can be reached at [email protected]/[email protected]/[email protected]