Low-complexity Linear Multicast Beamforming for Cache-aided MIMO Communications

Mohammad NaseriTehrani, MohammadJavad Salehi, Antti Tölli
Computer Science, Information Theory, Information Theory (cs.IT), Signal Processing (eess.SP)
2023-12-05 00:00:00
A practical and scalable multicast beamformer design in multi-input multi-output~(MIMO) coded caching~(CC) systems is introduced in this paper. The proposed approach allows multicast transmission to multiple groups with partially overlapping user sets using receiver dimensions to distinguish between different group-specific streams. Additionally, it provides flexibility in accommodating various parameter configurations of the MIMO-CC setup and overcomes practical limitations, such as the requirement to use successive interference cancellation~(SIC) at the receiver, while achieving the same degrees-of-freedom~(DoF). To evaluate the proposed scheme, we define the symmetric rate as the sum rate of the partially overlapping streams received per user, comprising a linear multistream multicast transmission vector and the linear minimum mean square error~(LMMSE) receiver. The resulting non-convex symmetric rate maximization problem is solved using alternative optimization and successive convex approximation~(SCA). Moreover, a fast iterative Lagrangian-based algorithm is developed, significantly reducing the computational overhead compared to previous designs. The effectiveness of our proposed method is demonstrated by extensive simulations.
PDF: Low-complexity Linear Multicast Beamforming for Cache-aided MIMO Communications.pdf
Empowered by ChatGPT