Performance Analysis of Dual-User Macrodiversity MIMO Systems with Linear Receivers in Flat Rayleigh Fading

Abstract

The performance of linear receivers in the presence of co-channel interference in Rayleigh channels is a fundamental problem in wireless communications. Performance evaluation for these systems is well-known for receive arrays where the antennas are close enough to experience equal average SNRs from a source. In contrast, almost no analytical results are available for macrodiversity systems where both the sources and receive antennas are widely separated. Here, receive antennas experience unequal average SNRs from a source and a single receive antenna receives a different average SNR from each source. Although this is an extremely difficult problem, progress is possible for the two-user scenario. In this paper, we derive closed form results for the probability density function (pdf) and cumulative distribution function (cdf) of the output signal to interference plus noise ratio (SINR) and signal to noise ratio (SNR) of minimum mean squared error (MMSE) and zero forcing (ZF) receivers in independent Rayleigh channels with arbitrary numbers of receive antennas. The results are verified by Monte Carlo simulations and high SNR approximations are also derived. The results enable further system analysis such as the evaluation of outage probability, bit error rate (BER) and capacity.

Performance Analysis of Macrodiversity MIMO Systems with MMSE and ZF Receivers in Flat Rayleigh Fading

“…The high SNR expression derived in (47) will be exact, if and only ifK 0 is exact. An exact calculation ofK 0 for the N = 2 case is presented in [26] and shown to have a complex expression. This work suggests that in the general case an exact calculation is likely to be either excessively complicated or intractable.…”

“…An exact analysis of ( 24) is extremely cumbersome. However, for the dual source scenario where N = 2, (24) can be solved in closed form [26]. Even for N = 2, the resulting exact expressions are complex.…”

Large-scale cloud radio access networks: Fundamental asymptotic analysis

“…where the first asymptotic equality comes from the fact that the cross term is asymptotically ignorable and the last equality comes from inserting (12). Define L k as the set of BSs sufficiently near user k, given by…”

“…where the first asymptotic equality comes from the fact that the cross term is asymptotically ignorable and the third equality is obtained by inserting (12). Note that ψ mrt kk = ψ if kk so that the SNR scaling exponent of MRT operation is the same as that of IF operation.…”

“…Although the performance of an LS-CRAN has been widely investigated in literature [9], [11] via simulations, an intuitive analytic result considering practical limitations is not available yet. The exact distribution of the signal-to-interference-plusnoise ratio (SINR) of the MRT or ZF operation is derived in [12] for the case of two distributed BSs and its Laplace approximated distribution is derived in [13] for a general LS-CRAN. In [14], a simpler form of the SINR distribution is derived by approximating the SINR as a Gamma random variable.…”