TY - GEN
T1 - Robust Group Testing-Based Multiple-Access Protocol for Massive MIMO
AU - Vershinin, George
AU - Cohen, Asaf
AU - Gurewitz, Omer
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - With the ever-increasing demand for more per-household devices and the addition of more antennas per device, the challenge of effective scheduling and resource sharing to access the wireless shared channel for uplink communication with the base station (BS) becomes daunting. To address this issue, we devise and study a robust multiple-access protocol for massive multiple-input-multiple-output (MIMO) systems, based on sparse coding techniques originated in group testing (GT), for systems with non-cooperative self-scheduling users with reduced complexity and no scheduling overhead. In this study, we analyze our scheme’s bit-error rate, decoding error probability, scaling laws, system sum-rate, and complexity. We show that our suggested scheme is order-optimal by comparing our sum-rate with the perfect channel state information (CSI) model and numerically evaluate how our system scales with an increasing number of active devices and signal-to-noise ratio (SNR).
AB - With the ever-increasing demand for more per-household devices and the addition of more antennas per device, the challenge of effective scheduling and resource sharing to access the wireless shared channel for uplink communication with the base station (BS) becomes daunting. To address this issue, we devise and study a robust multiple-access protocol for massive multiple-input-multiple-output (MIMO) systems, based on sparse coding techniques originated in group testing (GT), for systems with non-cooperative self-scheduling users with reduced complexity and no scheduling overhead. In this study, we analyze our scheme’s bit-error rate, decoding error probability, scaling laws, system sum-rate, and complexity. We show that our suggested scheme is order-optimal by comparing our sum-rate with the perfect channel state information (CSI) model and numerically evaluate how our system scales with an increasing number of active devices and signal-to-noise ratio (SNR).
KW - Group Testing
KW - Massive MIMO
KW - Multiple-Access
UR - http://www.scopus.com/inward/record.url?scp=85164941098&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-34671-2_15
DO - 10.1007/978-3-031-34671-2_15
M3 - Conference contribution
AN - SCOPUS:85164941098
SN - 9783031346705
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 200
EP - 215
BT - Cyber Security, Cryptology, and Machine Learning - 7th International Symposium, CSCML 2023, Proceedings
A2 - Dolev, Shlomi
A2 - Gudes, Ehud
A2 - Paillier, Pascal
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023
Y2 - 29 June 2023 through 30 June 2023
ER -