Communication channel

About: Communication channel is a research topic. Over the lifetime, 137411 publications have been published within this topic receiving 1715077 citations. The topic is also known as: communication channel & communications channel.

General nonasymptotic and asymptotic formulas in channel resolvability and identification capacity and their application to the wiretap channel

Abstract: Several nonasymptotic formulas are established in channel resolvability and identification capacity, and they are applied to the wiretap channel. By using these formulas, the epsi capacities of the above three problems are considered in the most general setting, where no structural assumptions such as the stationary memoryless property are made on a channel. As a result, we solve an open problem proposed by Han and Verduacute. Moreover, we obtain lower bounds of the exponents of error probability and the wiretapper's information in the wiretap channel

A Learning Theoretic Approach to Energy Harvesting Communication System Optimization

Abstract: A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov processes. Delay-limited communication is considered assuming that the underlying channel is block fading with memory, and the instantaneous channel state information is available at both the transmitter and the receiver. The expected total transmitted data during the transmitter's activation time is maximized under three different sets of assumptions regarding the information available at the transmitter about the underlying stochastic processes. A learning theoretic approach is introduced, which does not assume any a priori information on the Markov processes governing the communication system. In addition, online and offline optimization problems are studied for the same setting. Full statistical knowledge and causal information on the realizations of the underlying stochastic processes are assumed in the online optimization problem, while the offline optimization problem assumes non-causal knowledge of the realizations in advance. Comparing the optimal solutions in all three frameworks, the performance loss due to the lack of the transmitter's information regarding the behaviors of the underlying Markov processes is quantified.

Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer

Abstract: This paper studies a wireless-energy-transfer (WET) enabled massive multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid data-and-energy access point (H-AP) and multiple single-antenna users. In the WET-MM system, the H-AP is equipped with a large number $M$ of antennas and functions like a conventional AP in receiving data from users, but additionally supplies wireless power to the users. We consider frame-based transmissions. Each frame is divided into three phases: the uplink channel estimation (CE) phase, the downlink WET phase, as well as the uplink wireless information transmission (WIT) phase. Firstly, users use a fraction of the previously harvested energy to send pilots, while the H-AP estimates the uplink channels and obtains the downlink channels by exploiting channel reciprocity. Next, the H-AP utilizes the channel estimates just obtained to transfer wireless energy to all users in the downlink via energy beamforming. Finally, the users use a portion of the harvested energy to send data to the H-AP simultaneously in the uplink (reserving some harvested energy for sending pilots in the next frame). To optimize the throughput and ensure rate fairness, we consider the problem of maximizing the minimum rate among all users. In the large-$M$ regime, we obtain the asymptotically optimal solutions and some interesting insights for the optimal design of WET-MM system. We define a metric, namely, the massive MIMO degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by $\log(M)$. We show that the proposed WET-MM system is optimal in terms of MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.

A stochastic multiple-input-multiple-output radio channel model for evaluation of space-time coding algorithms

Abstract: A simple framework for Monte Carlo simulations of a multiple-input-multiple-output radio channel is proposed. The derived model includes the partial correlation between the paths in the channel, as well as fast fading and time dispersion. The only input parameters required for the model are the shape of the power delay spectrum and the spatial correlation functions at the transmit and receive end. Thus, the required parameters are available in the open literature for a large variety of environments. It is furthermore demonstrated that the Shannon capacity of the channel is highly dependent on the considered environment.

ARQ error control for fading mobile radio channels

Abstract: In this paper, we study the correlation properties of the fading mobile radio channel Based on these studies, we model the channel as a one-step Markov process whose transition probabilities are a function of the channel characteristics Then we present the throughput performance of the Go-Back-N and selective-repeat automatic repeat request (ARQ) protocols with timer control, using the Markov model for both forward and feedback channels This approximation is found to be very good, as confirmed by simulation results