All Dates/Times are Australian Eastern Standard Time (AEST)

Technical Program

Paper Detail

Paper IDD6-S1-T1.1
Paper Title Near-Optimal Coding for Massive Multiple Access
Authors Kuan Hsieh, University of Cambridge, United Kingdom; Cynthia Rush, Columbia University, United States; Ramji Venkataramanan, University of Cambridge, United Kingdom
Session D6-S1-T1: Massive Multiple Access Channels
Chaired Session: Monday, 19 July, 22:00 - 22:20
Engagement Session: Monday, 19 July, 22:20 - 22:40
Abstract We study the Gaussian multiple access channel (MAC) in the asymptotic regime where the number of users grows linearly with the codelength. We analyze coding schemes based on random linear models with approximate message passing (AMP) decoding. For fixed target error rate and number of bits per user, we obtain the exact tradeoff between energy-per-bit and the user density achievable in the large system limit. We show that a spatially coupled coding scheme with AMP decoding achieves near-optimal tradeoff for a large range of user densities. We also study the spectral efficiency versus energy-per-bit tradeoff in the regime where the number of bits per user is large.