Computer Science – Information Theory
Scientific paper
2008-06-16
Computer Science
Information Theory
This work in part was presented in IEEE PIMRC'2008, Cannes, France, September 2008
Scientific paper
In our recent work, we reported an exhaustive study on the simulated bit error rate (BER) performance of a low-complexity likelihood ascent search (LAS) algorithm for detection in large multiple-input multiple-output (MIMO) systems with large number of antennas that achieve high spectral efficiencies. Though the algorithm was shown to achieve increasingly closer to near maximum-likelihood (ML) performance through simulations, no BER analysis was reported. Here, we extend our work on LAS and report an asymptotic BER analysis of the LAS algorithm in the large system limit, where $N_t,N_r \to \infty$ with $N_t=N_r$, where $N_t$ and $N_r$ are the number of transmit and receive antennas. We prove that the error performance of the LAS detector in V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the ML detector as $N_t,N_r \to \infty$.
Chockalingam Ananthanarayanan
Mohammed Saif K.
Rajan Sundar B.
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