The information theoretic capacity of a single user distributed wireless communication system (DWCS) is investigated and compared to that of traditional cellular MIMO system. Simulation results show that, DWCS always outperforms traditional MIMO system, and the capacity gain increase with the incremental number of the fixed antennas. Moreover, the use of distributed antennas in DWCS can average the shadowing effect and solve the near-far problem efficiently.
This article explores a method of creating confidence bounds for information-theoretic measures in linguistics, such as entropy, Kullback-Leibler Divergence (KLD), and mutual information. We show that a useful measure of uncertainty can be derived from simple statistical principles, namely the asymptotic distribution of the maximum likelihood estimator (MLE) and the delta method. Three case studies from phonology and corpus linguistics are used to demonstrate how to apply it and examine its robustness against common violations of its assumptions in linguistics, such as insufficient sample size and non-independence of data points.
Capacity Analysis and Simulations of Distributed Wireless Communication System
