QoS-Aware User Scheduling in Crowded XL-MIMO Systems Under Non-Stationary Multi-State LoS/NLoS Channels

Ensuring that the quality-of-service (QoS) requirements are satisfied in wireless communications systems with high user density is challenging due to the limitations on the transmit power budget and the number of resource blocks. In this paper, we propose a QoS-aware joint user scheduling and power allocation technique to enhance the number of served users in the downlink of crowded extra-large scale massive multiple-input multiple-output (XL-MIMO) with minimum QoS requirements guarantee. The proposed technique is constituted by two sequential procedures: the clique search-based scheduling (CBS) algorithm for user scheduling followed by optimal power allocation with transmit power budget and minimum achievable rate per user constraints.We propose a generalized non-stationary multi-state channel model based on spherical wave propagation assuming that users under line-of-sight (LoS) and non-LoS (NLoS) transmission coexist in the same communication cell. This is done to accurately evaluate the proposed technique in realistic XL-MIMO scenarios. Numerical results reveal that the proposed CBS algorithm provides fair coverage over the whole cell area, achieving remarkable numbers of scheduled users with satisfied QoS requirements when users under the LoS and NLoS channel states coexist in the communication cell.

[1]  Zhaocheng Wang,et al.  Downlink Resource Allocation With Pilot Length Optimization for User-Centric Cell-Free MIMO Networks , 2022, IEEE Communications Letters.

[2]  Wei Yu,et al.  Learning Based User Scheduling in Reconfigurable Intelligent Surface Assisted Multiuser Downlink , 2022, IEEE Journal of Selected Topics in Signal Processing.

[3]  Haiquan Lu,et al.  Near-Field Modeling and Performance Analysis for Multi-User Extremely Large-Scale MIMO Communication , 2022, IEEE Communications Letters.

[4]  R. Tafazolli,et al.  A Non-Stationary Channel Model with Correlated NLoS/LoS States for ELAA-mMIMO , 2021, 2021 IEEE Global Communications Conference (GLOBECOM).

[5]  Linglong Dai,et al.  Channel Estimation for Extremely Large-Scale MIMO: Far-Field or Near-Field? , 2021, IEEE Transactions on Communications.

[6]  Luis Castedo,et al.  Low-Complexity Distance-Based Scheduling for Multi-User XL-MIMO Systems , 2021, IEEE Wireless Communications Letters.

[7]  Petar Popovski,et al.  Quasi-Distributed Antenna Selection for Spectral Efficiency Maximization in Subarray Switching XL-MIMO Systems , 2021, IEEE Transactions on Vehicular Technology.

[8]  Yong Zeng,et al.  How Does Performance Scale with Antenna Number for Extremely Large-Scale MIMO? , 2020, ICC 2021 - IEEE International Conference on Communications.

[9]  Hoang Duong Tuan,et al.  Energy-Efficient Multi-Cell Massive MIMO Subject to Minimum User-Rate Constraints , 2020, IEEE Transactions on Communications.

[10]  Taufik Abrão,et al.  Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems , 2020, IEEE Transactions on Vehicular Technology.

[11]  Elisabeth de Carvalho,et al.  A Message Passing Based Receiver for Extra-Large Scale MIMO , 2019, 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[12]  Shi Jin,et al.  Channel Estimation for Extremely Large-Scale Massive MIMO Systems , 2019, IEEE Wireless Communications Letters.

[13]  Robert W. Heath,et al.  Non-Stationarities in Extra-Large-Scale Massive MIMO , 2019, IEEE Wireless Communications.

[14]  Taufik Abrão,et al.  Collision Resolution Protocol via Soft Decision Retransmission Criterion , 2019, IEEE Transactions on Vehicular Technology.

[15]  Adão Silva,et al.  An Overview on Resource Allocation Techniques for Multi-User MIMO Systems , 2016, IEEE Communications Surveys & Tutorials.

[16]  Peng Wang,et al.  Performance Impact of LoS and NLoS Transmissions in Dense Cellular Networks , 2015, IEEE Transactions on Wireless Communications.

[17]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[18]  Daniel Pérez Palomar,et al.  Practical algorithms for a family of waterfilling solutions , 2005, IEEE Transactions on Signal Processing.

[19]  José Carlos Marinello Filho,et al.  Exploring the Non-Overlapping Visibility Regions in XL-MIMO Random Access and Scheduling , 2022, IEEE Transactions on Wireless Communications.

[20]  R. Shafin,et al.  Angle-based Downlink Beam Selection and User Scheduling for Massive MIMO Systems , 2022, IEEE Transactions on Wireless Communications.

[21]  Andrea J. Goldsmith,et al.  Sum-rate optimal multi-antenna downlink beamforming strategy based on clique search , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..