Effects of channel state information uncertainty on the performance of stochastic signaling

In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, it is shown that, for a given decision rule at the receiver, stochastic signaling based on the available CSI at the transmitter results in a randomization between at most two different signal levels for each symbol. Then, the performance of stochastic signaling and conventional deterministic signaling is compared, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Finally a numerical example is presented to explore the theoretical results. © 2011 IEEE

Stochastic signaling in the presence of channel state information uncertainty

Cataloged from PDF version of article.In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results. (C) 2012 Elsevier Inc. All rights reserve

Energy-efficient coding with discrete stochastic events

We investigate the energy efficiency of signaling mechanisms that transfer information by means of discrete stochastic events, such as the opening or closing of an ion channel. Using a simple model for the generation of graded electrical signals by sodium and potassium channels, we find optimum numbers of channels that maximize energy efficiency. The optima depend on several factors: the relative magnitudes of the signaling cost (current flow through channels), the fixed cost of maintaining the system, the reliability of the input, additional sources of noise, and the relative costs of upstream and downstream mechanisms. We also analyze how the statistics of input signals influence energy efficiency. We find that energy-efficient signal ensembles favor a bimodal distribution of channel activations and contain only a very small fraction of large inputs when energy is scarce. We conclude that when energy use is a significant constraint, trade-offs between information transfer and energy can strongly influence the number of signaling molecules and synapses used by neurons and the manner in which these mechanisms represent information

Fundamentals of Heterogeneous Cellular Networks with Energy Harvesting

We develop a new tractable model for K-tier heterogeneous cellular networks (HetNets), where each base station (BS) is powered solely by a self-contained energy harvesting module. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deployment density. Since a BS may not always have enough energy, it may need to be kept OFF and allowed to recharge while nearby users are served by neighboring BSs that are ON. We show that the fraction of time a k^{th} tier BS can be kept ON, termed availability \rho_k, is a fundamental metric of interest. Using tools from random walk theory, fixed point analysis and stochastic geometry, we characterize the set of K-tuples (\rho_1, \rho_2, ... \rho_K), termed the availability region, that is achievable by general uncoordinated operational strategies, where the decision to toggle the current ON/OFF state of a BS is taken independently of the other BSs. If the availability vector corresponding to the optimal system performance, e.g., in terms of rate, lies in this availability region, there is no performance loss due to the presence of unreliable energy sources. As a part of our analysis, we model the temporal dynamics of the energy level at each BS as a birth-death process, derive the energy utilization rate, and use hitting/stopping time analysis to prove that there exists a fundamental limit on \rho_k that cannot be surpassed by any uncoordinated strategy.Comment: submitted to IEEE Transactions on Wireless Communications, July 201