TY - GEN
T1 - Low-Rank Optimization for Topological Interference Alignment in MIMO Networks
AU - Liu, Xuan
AU - Zhang, Wenhao
AU - Xu, Zhao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/8/20
Y1 - 2024/8/20
N2 - In dense networks, interference becomes the main bottleneck for achieving high data rates. Topological interference management (TIM) is proposed to manage interference only based on network topology information to reduce the system overhead. In this paper we study the TIM problem in the multiple-input multiple-output (MIMO) interference channel with only the network connectivity information. For the general asymmetric channel with Mi antennas at each transmitter and Ni antennas at each receiver, we provide a topological interference alignment condition via carefully designing the structured transceivers. It turns out that the achievable degrees-of-freedom (DoFs) for each user grow linearly with {Mi, Ni}. We further present a low-rank optimization approach to maximize the achievable DoFs, followed by developing a novel difference-of-convex programming algorithm with convergence guarantees. Numerical results demonstrate the effectiveness of the proposed methods for topological interference management in MIMO networks.
AB - In dense networks, interference becomes the main bottleneck for achieving high data rates. Topological interference management (TIM) is proposed to manage interference only based on network topology information to reduce the system overhead. In this paper we study the TIM problem in the multiple-input multiple-output (MIMO) interference channel with only the network connectivity information. For the general asymmetric channel with Mi antennas at each transmitter and Ni antennas at each receiver, we provide a topological interference alignment condition via carefully designing the structured transceivers. It turns out that the achievable degrees-of-freedom (DoFs) for each user grow linearly with {Mi, Ni}. We further present a low-rank optimization approach to maximize the achievable DoFs, followed by developing a novel difference-of-convex programming algorithm with convergence guarantees. Numerical results demonstrate the effectiveness of the proposed methods for topological interference management in MIMO networks.
KW - difference-of-convex programming
KW - low-rank optimization
KW - multiple-input multiple-output channel
KW - Topological interference management
UR - https://www.scopus.com/pages/publications/85202808648
U2 - 10.1109/ICC51166.2024.10622889
DO - 10.1109/ICC51166.2024.10622889
M3 - Conference article published in proceeding or book
AN - SCOPUS:85202808648
T3 - IEEE International Conference on Communications
SP - 3883
EP - 3887
BT - ICC 2024 - IEEE International Conference on Communications
A2 - Valenti, Matthew
A2 - Reed, David
A2 - Torres, Melissa
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 59th Annual IEEE International Conference on Communications, ICC 2024
Y2 - 9 June 2024 through 13 June 2024
ER -