TY - GEN
T1 - Rate Splitting for General Multicast
AU - Zhao, Lingzhi
AU - Cui, Ying
AU - Yang, Sheng
AU - Shamai Shitz, Shlomo
AU - Han, Yunbo
AU - Zhang, Yunfei
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates the optimization of general rate splitting with linear beamforming for general multicast. Specifically, we consider a multi-carrier single-cell wireless network where a multi-antenna base station (BS) communicates to multiple single-antenna users via general multicast. Linear beamforming is adopted at the BS, and joint decoding is adopted at each user. We consider the maximization of the weighted sum rate, which is a challenging nonconvex problem. Then, we propose an iterative algorithm for the problem to obtain a KKT point using the concave-convex procedure (CCCP). The proposed optimization framework generalizes the existing ones for rate splitting for various types of services. Finally, we numerically show substantial gains of the proposed solutions over existing schemes and reveal the design insights of general rate splitting for general multicast.
AB - Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates the optimization of general rate splitting with linear beamforming for general multicast. Specifically, we consider a multi-carrier single-cell wireless network where a multi-antenna base station (BS) communicates to multiple single-antenna users via general multicast. Linear beamforming is adopted at the BS, and joint decoding is adopted at each user. We consider the maximization of the weighted sum rate, which is a challenging nonconvex problem. Then, we propose an iterative algorithm for the problem to obtain a KKT point using the concave-convex procedure (CCCP). The proposed optimization framework generalizes the existing ones for rate splitting for various types of services. Finally, we numerically show substantial gains of the proposed solutions over existing schemes and reveal the design insights of general rate splitting for general multicast.
KW - General multicast
KW - concave-convex procedure (CCCP)
KW - general rate splitting
KW - joint decoding
KW - linear beamforming
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85137259588&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICC45855.2022.9838824
DO - https://doi.org/10.1109/ICC45855.2022.9838824
M3 - منشور من مؤتمر
T3 - IEEE International Conference on Communications
SP - 3936
EP - 3941
BT - ICC 2022 - IEEE International Conference on Communications
T2 - 2022 IEEE International Conference on Communications, ICC 2022
Y2 - 16 May 2022 through 20 May 2022
ER -