Capacity of MIMO channels: asymptotic evaluation under correlated fading

Abstract

Abstract-This paper investigates the asymptotic uniform power allocation capacity of frequency nonselective multiple-input multiple-output channels with fading correlation at either the transmitter or the receiver. We consider the asymptotic situation, where the number of inputs and outputs increase without bound at the same rate. A simple uniparametric model for the fading correlation function is proposed and the asymptotic capacity per antenna is derived in closed form. Although the proposed correlation model is introduced only for mathematical convenience, it is shown that its shape is very close to an exponentially decaying correlation function. The asymptotic expression obtained provides a simple and yet useful way of relating the actual fading correlation to the asymptotic capacity per antenna from a purely analytical point of view. For example, the asymptotic expressions indicate that fading correlation is more harmful when arising at the side with less antennas. Moreover, fading correlation does not influence the rate of growth of the asymptotic capacity per receive antenna with high 0 . Index Terms-Correlated fading, free probability, multipleinput multiple-output (MIMO) capacity, random matrix theory.

Combined Beamforming With Alamouti Coding Using Double Antenna Array Group for Multiuser Interference Cancellation

“…We shall consider correlated channel conditions influence on the bit-error-rate (BER) performance firstly. The channel matrix is modeled as [17][18][19] …”

Eigenvalue based SNR estimation for cognitive radio in presence of channel correlation

“…For modeling channel correlation, we use the one-sided correlation model as in [11]. In this paper, we focus on the correlation across channel receive dimensions and not on the temporal correlation.…”

“…Theorem 3.1: [11] Let Θ be a positive definite matrix which is normalized as: (1/M )trace{Θ} = 1, and whose asymptotic spectrum has the p.d.f.…”

“…In (9), the parameter µ controls the degree of covariance and varies the support of the distribution i.e., for µ = 0,ã = a andb = b, where a = (1 − √ β) 2 and b = (1 + √ β) 2 are the supports of the MP distribution [8]. For the exponential covariance model as stated in [11], the parameter µ is related to the correlation coefficient ς with the following relation: µ = ς 2 1−ς 2 . Furthermore, the SCN is related to ς with the relation SCN = 1+ς 1−ς .…”

“…RMT has been used in the literature in various applications such as modeling transmit/receive correlation in Multiple Input Multiple Output (MIMO) channels and multiuser MIMO fading [10,11]. In the existing literature, RMT has received attention in the CR research community, specifically in the SS research area [7,12].…”