Optimization of computational resource allocation for soft MIMO detection
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
| Hi-index | 0.00 |
It is well known that linear MMSE can outperform its zero-forcing counterpart. In combination with a successive interference canceller, MMSE can fully exploit the capacity of MIMO (multiple-input-multiple-output) channels [A.J. Viterbi, 1986, M.K. Varanasi, T. Guess, 1997]. In practice, however, such an advantage is compromised due to its implementation complexity and the requirement of accurate SNR estimate. Thus other equalizers such as zero-forcing may present an attractive alternative as long as the performance gap is tolerable. This motivates a need to quantify the tradeoff between MMSE and zero-forcing in both parallel and sequential structures. In this paper, the capacity performance of different equalization schemes is investigated, with closed-form formulas provided in terms of two key measures: capacity gaps and ratios. We also conclude that the capacity gain via structural choice (between parallel and sequential) far out-weights that via filter choice (between zero-forcing and MMSE). Indeed, the latter is found to be almost negligible for most practical SNR regions. It is also shown that the sequential zero-forcing equalizers can asymptotically reach the channel capacity when SNR approaches infinity, irrelevant of the detection order. Although this paper is focused on the flat-fading channels, the result is directly extendable to the ISI case by slicing the frequency band into infinitesimal stripes, each of which can be treated as flat.