Statistical mechanical analysis of the linear vector channel in digital communication

Abstract

A statistical mechanical framework to analyze linear vector channel models in digital wireless communication is proposed for a large system. The framework is a generalization of that proposed for code-division multiple-access systems in Europhys. Lett. 76 (2006) 1193 and enables the analysis of the system in which the elements of the channel transfer matrix are statistically correlated with each other. The significance of the proposed scheme is demonstrated by assessing the performance of an existing model of multi-input multi-output communication systems.

15 pages, 2 figures

References in corpus (5)

• Replica Field Theory for Deterministic Models (II): A Non-Random Spin Glass with Glassy Behavior
• Mean-Field Equations for Spin Models with Orthogonal Interaction Matrices
• Analysis of CDMA systems that are characterized by eigenvalue spectrum
• Tractable approximations for probabilistic models: The adaptive TAP mean field approach
• The role of the interaction matrix in mean-field spin glasses

Cited by in corpus (4)

• Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels
• Perceptron capacity revisited: classification ability for correlated patterns
• Statistical mechanical analysis of the Kronecker channel model for MIMO wireless communication
• Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach