Conditional Entropy based User Selection for Multiuser MIMO Systems

We consider the problem of user subset selection for maximizing the sum rate of downlink multi-user MIMO systems. The brute-force search for the optimal user set becomes impractical as the total number of users in a cell increase. We propose a user selection algorithm based on conditional differential entropy. We apply the proposed algorithm on Block diagonalization scheme. Simulation results show that the proposed conditional entropy based algorithm offers better alternatives than the existing user selection algorithms. Furthermore, in terms of sum rate, the solution obtained by the proposed algorithm turns out to be close to the optimal solution with significantly lower computational complexity than brute-force search.Comment: 4 pages, 3 figure

User Selection in MIMO Interfering Broadcast Channels

Interference alignment aims to achieve maximum degrees of freedom in an interference system. For achieving Interference alignment in interfering broadcast systems a closed-form solution is proposed in [1] which is an extension of the grouping scheme in [2]. In a downlink scenario where there are a large number of users, the base station is required to select a subset of users such that the sum rate is maximized. To search for the optimal user subset using brute-force approach is computationally exhaustive because of the large number of possible user subset combinations. We propose a user selection algorithm achieving sum rate close to that of optimal solution. The algorithm employs coordinate ascent approach and exploits orthogonality between the desired signal space and the interference channel space in the reciprocal system to select the user at each step. For the sake of completeness, we have also extended the sum rate approach based algorithm to Interfering broadcast channel. The complexity of both these algorithms is shown to be linear with respect to the total number of users as compared to exponential in brute-force search.Comment: 9 pages, 5 figure

Objective Information Theory: A Sextuple Model and 9 Kinds of Metrics

In the contemporary era, the importance of information is undisputed, but there has never been a common understanding of information, nor a unanimous conclusion to the researches on information metrics. Based on the previous studies, this paper analyzes the important achievements in the researches of the properties and metrics of information as well as their main insufficiencies, and explores the essence and connotation, the mathematical expressions and other basic problems related to information. On the basis of the understanding of the objectivity of information, it proposes the definitions and a Sextuple model of information; discusses the basic properties of information, and brings forward the definitions and mathematical expressions of nine kinds of metrics of information, i.e., extensity, detailedness, sustainability, containability, delay, richness, distribution, validity and matchability. Through these, this paper establishes a basic theory frame of Objective Information Theory to support the analysis and research on information and information system systematically and comprehensively.Comment: 20 page