Percentile Optimization in Wireless Networks- Part II: Beamforming for Cell-Edge Throughput Maximization
<|reference_start|>Percentile Optimization in Wireless Networks- Part II: Beamforming for Cell-Edge Throughput Maximization: Part I of this two-part paper focused on the formulation of percentile problems, complexity analysis, and development of power control algorithms via the quadratic fractional transform (QFT) and logarithmic fractional transform (LFT) for sum-least-qth-percentile (SLqP) rate maximization problems. In this second part, we first tackle the significantly more challenging problems of optimizing SLqP rate via beamforming in a multiuser, multiple-input multiple-output (MU- MIMO) network to maximize cell-edge throughput. To this end, we first propose an adaptation of the QFT algorithm presented in Part I that enables optimization of the complex-valued multidimensional beamforming weights for the SLqP rate utility function. We also introduce a new class of problems which we term as sum-greatest-qth-percentile weighted mean squared error (SGqP-WMSE) minimization. We show that this class subsumes the well-known sum-weighted mean squared error (WMMSE) minimization and max-WMSE minimization problems. We demonstrate an equivalence between this class of problems and the SLqP rate maximization problems, and show that this correspondence can be exploited to obtain stationary-point solutions for the aforementioned beamforming problem. Next, we develop extensions for the QFT and LFT algorithms from Part I to optimize ergodic long-term average or ergodic SLqP utility. Finally, we also consider related problems which can be solved using the proposed techniques, including hybrid utility functions targeting optimization at specific subsets of users within cellular networks.<|reference_end|>
@article{khan2024percentile,
    title={Percentile Optimization in Wireless Networks- Part II: Beamforming for
  Cell-Edge Throughput Maximization},
    author={Ahmad Ali Khan and Raviraj Adve},
    journal={arXiv preprint arXiv:2403.16343},
    year={2024},
    doi={10.1109/TSP.2024.3372252},
    archivePrefix={arXiv},
    eprint={2403.16343},
    primaryClass={cs.IT math.IT}
}