BOOST: Base station on-off switching strategy for energy efficient massive MIMO HetNets
Mingjie Feng, Shiwen Mao, and Tao Jiang

TL;DR
This paper proposes energy-efficient base station on-off switching and user association strategies in massive MIMO HetNets, using centralized and distributed schemes to optimize energy efficiency with proven convergence and significant gains.
Contribution
It introduces a novel joint BS on-off and user association framework for massive MIMO HetNets, with both centralized and distributed solutions and theoretical convergence guarantees.
Findings
Significant energy efficiency improvements over benchmarks
Centralized scheme achieves optimal solutions via LP relaxation
Distributed bidding game converges to Nash Equilibrium
Abstract
In this paper, we investigate the problem of optimal base station (BS) ON-OFF switching and user association in a heterogeneous network (HetNet) with massive MIMO, with the objective to maximize the system energy efficiency (EE). The joint BS ON-OFF switching and user association problem is formulated as an integer programming problem. We first develop a centralized scheme, in which we relax the integer constraints and employ a series of Lagrangian dual methods that transform the original problem into a standard linear programming (LP) problem. Due to the special structure of the LP, we prove that the optimal solution to the relaxed LP is also feasible and optimal to the original problem. We then propose a distributed scheme by formulating a repeated bidding game for users and BS's, and prove that the game converges to a Nash Equilibrium (NE). Simulation studies demonstrate that the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
