TY - GEN
T1 - Deep Learning Based Modulation for Quantized SIMO Communications
AU - Khalili, Abbas
AU - Erkip, Elza
N1 - Funding Information:
The work supported in part by NSF grant 1547332, and by InterDigital.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - High resolution analog to digital converters (ADCs) are major sources of power consumption in conventional fully digital receivers. To reduce power consumption, it is suggested to use a small number of low resolution ADCs. However, for a given number of low resolution ADCs, the best modulation scheme and corresponding quantization strategy that maximizes the spectral efficiency are still unknown. In this paper, a point-to-point singleinput multiple-output system with a hybrid receiver using low resolution ADCs is considered. A novel deep learning based modulation scheme and the associated quantization strategy are developed to maximize the spectral efficiency. It is observed that the derived modulation scheme can achieve optimal high SNR rates and perform near Shannon capacity at low and intermediate SNRs. Our results provide new insights into the optimal utilization of low resolution ADCs and optimal power-performance trade-off in terms of the spectral efficiency.
AB - High resolution analog to digital converters (ADCs) are major sources of power consumption in conventional fully digital receivers. To reduce power consumption, it is suggested to use a small number of low resolution ADCs. However, for a given number of low resolution ADCs, the best modulation scheme and corresponding quantization strategy that maximizes the spectral efficiency are still unknown. In this paper, a point-to-point singleinput multiple-output system with a hybrid receiver using low resolution ADCs is considered. A novel deep learning based modulation scheme and the associated quantization strategy are developed to maximize the spectral efficiency. It is observed that the derived modulation scheme can achieve optimal high SNR rates and perform near Shannon capacity at low and intermediate SNRs. Our results provide new insights into the optimal utilization of low resolution ADCs and optimal power-performance trade-off in terms of the spectral efficiency.
UR - http://www.scopus.com/inward/record.url?scp=85150198676&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85150198676&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF56349.2022.10051905
DO - 10.1109/IEEECONF56349.2022.10051905
M3 - Conference contribution
AN - SCOPUS:85150198676
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 709
EP - 714
BT - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Y2 - 31 October 2022 through 2 November 2022
ER -