Abstract
This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels. Noticing that the existing definition of EE fails to account for group sizes, a new metric called multicast energy efficiency (MEE) is proposed. In this context, the joint design is considered for the maximization of MEE, EE, and scheduled users. Firstly, with the help of binary variables (associated with grouping and scheduling) the joint design problem is formulated as a mixed-Boolean fractional programming problem such that it facilitates the joint update of grouping, scheduling and precoding variables. Further, several novel optimization formulations are proposed to reveal the hidden difference of convex/ concave structure in the objective and associated constraints. Thereafter, we propose a convex-concave procedure framework based iterative algorithm for each optimization criteria where grouping, scheduling, and precoding variables are updated jointly in each iteration. Finally, we compare the performance of the three design criteria concerning three performance metrics namely MEE, EE, and scheduled users through Monte-Carlo simulations. These simulations establish the need for MEE and the improvement from the system optimization.
Highlights
The mobile data traffic is exploding unprecedentedly due to the exponential increase in mobile devices and their demand for throughput hungry service/ applications [3]
At the solution level, the problem is decoupled into user grouping and scheduling followed by semidefinite relaxation (SDR) based precoding which is likely to include high-rank matrices for multigroup multicasting (MGMC) systems [21]; the solutions may become infeasible to the original problems
In this paper, the joint design of user grouping, scheduling, and precoding problem was considered for the message-based multigroup multicast scenario in multiuser MISO downlink channels
Summary
The mobile data traffic is exploding unprecedentedly due to the exponential increase in mobile devices and their demand for throughput hungry service/ applications [3]. Noticing the drawbacks of existing EE definition, in this work, a new metric called multicast energy efficiency (MEE) is proposed to account for the group sizes along with the minimum rates. Realizing the importance of MEE, in this work, we consider the joint design of user grouping, scheduling, and precoding for MGMC systems subject to grouping, scheduling, quality-of-service (QoS) and total power constraints for the maximization of three design criteria: MEE, EE and scheduled users. In this context, related works in the literature and contributions/novelty of the paper are summarized in the sequel of this section
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