2016/08/11 by Wenbo He, He, Wenbo, Bobak Nazer +3 · 1 citation
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cooperative Communication and Network Coding #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1608.03351
openalex publication_date 2016/08/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Consider a Gaussian multiple-input multiple-output (MIMO) multiple-access channel (MAC) with channel matrix H and a Gaussian MIMO broadcast channel (BC) with channel matrix HT. For the MIMO MAC, the integer-forcing architecture consists of first decoding integer-linear combinations of the transmitted codewords, which are then solved for the original messages. For the MIMO BC, the integer-forcing architecture consists of pre-inverting the integer-linear combinations at the transmitter so that each receiver can obtain its desired codeword by decoding an integer-linear combination. In both cases, integer-forcing offers higher achievable rates than zero-forcing while maintaining a similar implementation complexity. This paper establishes an uplink-downlink duality relationship for integer-forcing, i.e., any sum rate that is achievable via integer-forcing on the MIMO MAC can be achieved via integer-forcing on the MIMO BC with the same sum power and vice versa. Using this duality relationship, it is shown that integer-forcing can operate within a constant gap of the MIMO BC sum capacity. Finally, the paper proposes a duality-based iterative algorithm for the non-convex problem of selecting optimal beamforming and equalization vectors, and establishes that it converges to a local optimum.