Name
Abstract | ||
|---|---|---|
This paper introduces a divide and conquer approach to the design of transmit and receive filters for communication over a Multiple Input Multiple Output (MIMO) Gaussian channel subject to an average power constraint. It involves conversion to a set of parallel scalar channels, possibly with very different gains, followed by coding per sub-channel (i.e. over time) rather than coding across sub-channels (i.e. over time and space). The loss in performance is negligible at high signal-to-noise ratio (SNR) and not significant at medium SNR. The advantages are reduction in signal processing complexity and greater insight into the SNR thresholds at which a channel is first allocated power. This insight is a consequence of formulating the optimal power allocation in terms of an upper bound on error rate that is determined by parameters of the input lattice such as the minimum distance and kissing number. The resulting thresholds are given explicitly in terms of these lattice parameters. By contrast, when the optimization problem is phrased in terms of maximizing mutual information, the solution is mercury waterfilling, and the thresholds are implicit. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5946351 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
Gaussian channels,MIMO communication,divide and conquer methods,error statistics,MIMO channel,divide and conquer approach,error rate,multiple input multiple output Gaussian channel,optimal power allocation,power constraint,receive filter,signal-to-noise ratio,transmit filter,Lattices,MIMO,error probability,mutual information,power allocation | Signal processing,Mathematical optimization,Computer science,Upper and lower bounds,Signal-to-noise ratio,Word error rate,Algorithm,Communication channel,MIMO,Theoretical computer science,Kissing number problem,Optimization problem | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4577-0537-3 | 978-1-4577-0537-3 | 1 |
PageRank | References | Authors |
0.38 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sreechakra Goparaju | 1 | 101 | 5.90 |
| A. R. Calderbank | 2 | 12550 | 2208.54 |
| William R. Carson | 3 | 53 | 3.34 |
| Miguel R. D. Rodrigues | 4 | 1500 | 111.23 |
| Fernando Pérez-Cruz | 5 | 749 | 61.24 |