Name
Abstract | ||
|---|---|---|
MIMO systems with several antennas at the transmitter and receiver have the potential to enable high throughputs. One of the challenges in realizing this potential is the design of receivers that scale in terms of computation and performance. Towards this end, in this paper, we propose a receiver that uses a committee of linear receivers, whose parameters are estimated from training data using a variant of the AdaBoost algorithm, a celebrated supervised classification algorithm in machine learning. We call our receiver boosted MMSE (B-MMSE) receiver and we study its performance via simulations. The channel matrix is estimated from the pilot using the MMSE technique. We find that for a 4 × 4 system with a Rayleigh fading channel, using BPSK at a bit error rate (BER) of 10-2, our receiver using the estimated channel matrix needs 2 dB less power than the plain MMSE receiver based on the estimated channel matrix. On an average, excluding the training phase, the receiver complexity equals 1.25 linear receivers. Thus the BMMSE receiver is slightly more complex than the MMSE receiver and substantially less complex than the maximum-likelihood receiver. We also show that the coded BER performance with an outer rate-3/4 Turbo-code has a gain of 5 dB at 10-4 coded BER when the demodulated output from the proposed method is used in place of plain MMSE detection with MMSE estimated channel. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/VTCFall.2013.6692120 | Vehicular Technology Conference |
Keywords | Field | DocType |
MIMO communication,antenna arrays,channel estimation,communication complexity,error statistics,least mean squares methods,radio receivers,radio transmitters,turbo codes,AdaBoost algorithm,B-MMSE receiver,BPSK,MIMO systems,MMSE detection,MMSE estimated channel,MMSE receivers,MMSE technique,antennas,bit error rate,boosted MMSE,channel matrix,coded BER performance,linear receivers,maximum-likelihood receiver,receiver complexity,training phase,transmitter,turbo code | Transmitter,AdaBoost,Rayleigh fading,Computer science,Turbo code,Communication channel,Electronic engineering,Boosting (machine learning),Bit error rate,Phase-shift keying | Conference |
ISSN | Citations | PageRank |
1090-3038 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Onkar Dabeer | 1 | 61 | 5.59 |
| Srinidhi Nagaraja | 2 | 0 | 0.34 |
| Chockalingam, A. | 3 | 0 | 0.68 |