Employing Antenna Selection to Improve Energy-Efficiency in Massive MIMO Systems

Massive MIMO systems promise high data rates by employing large number of antennas, which also increases the power usage of the system as a consequence. This creates an optimization problem which specifies how many antennas the system should employ in order to operate with maximal energy efficiency. Our main goal is to consider a base station with a fixed number of antennas, such that the system can operate with a smaller subset of antennas according to the number of active user terminals, which may vary over time. Thus, in this paper we propose an antenna selection algorithm which selects the best antennas according to the better channel conditions with respect to the users, aiming at improving the overall energy efficiency. Then, due to the complexity of the mathematical formulation, a tight approximation for the consumed power is presented, using the Wishart theorem, and it is used to find a deterministic formulation for the energy efficiency. Simulation results show that the approximation is quite tight and that there is significant improvement in terms of energy efficiency when antenna selection is employed.Comment: To appear in Transactions on Emerging Telecommunications Technologies, 12 pages, 8 figures, 2 table

Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems

This paper considers pilot design to mitigate pilot contamination and provide good service for everyone in multi-cell Massive multiple input multiple output (MIMO) systems. Instead of modeling the pilot design as a combinatorial assignment problem, as in prior works, we express the pilot signals using a pilot basis and treat the associated power coefficients as continuous optimization variables. We compute a lower bound on the uplink capacity for Rayleigh fading channels with maximum ratio detection that applies with arbitrary pilot signals. We further formulate the max-min fairness problem under power budget constraints, with the pilot signals and data powers as optimization variables. Because this optimization problem is non-deterministic polynomial-time hard due to signomial constraints, we then propose an algorithm to obtain a local optimum with polynomial complexity. Our framework serves as a benchmark for pilot design in scenarios with either ideal or non-ideal hardware. Numerical results manifest that the proposed optimization algorithms are close to the optimal solution obtained by exhaustive search for different pilot assignments and the new pilot structure and optimization bring large gains over the state-of-the-art suboptimal pilot design.Comment: 16 pages, 8 figures. Accepted to publish at IEEE Transactions on Wireless Communication

Joint Pilot Sequence Design and Power Control for Max-Min Fairness in Uplink Massive MIMO

This paper optimizes the pilot assignment and pilottransmit powers to mitigate pilot contamination in MassiveMIMO (multiple-input multiple-output) systems. While priorworks have treated pilot assignment as a combinatorial problem,we achieve a more tractable problem formulation by directlyoptimizing the pilot sequences. To this end, we compute alower bound on the uplink (UL) spectral efficiency (SE), forRayleigh fading channels with maximum ratio (MR) detectionand arbitrary pilot sequences. We optimize the max-min SEwith respect to the pilot sequences and pilot powers, under powerbudget constraints. This becomes an NP-hard signomial problem,but we propose an efficient algorithm to obtain a local optimumwith polynomial complexity. Numerical results manifest the nearoptimality of the proposed algorithm and show significant gainsover existing suboptimal algorithms.Funding agencies: European Unions Horizon research and innovation programme [641985]; ELLIIT; CENIITELLIITCENIIT5Gwireles