  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
$N_t,N_r \to \infty$.
