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Exploiting Underlay Spectrum Sharing in Cell-Free Massive MIMO Systems
- Publication Year :
- 2021
- Publisher :
- arXiv, 2021.
-
Abstract
- We investigate the coexistence of underlay spectrum sharing in cell-free massive multiple-input multiple-output (MIMO) systems. A primary system with geographically distributed primary access points (P-APs) serves a multitude of primary users (PUs), while a secondary system serves a large number of secondary users (SUs) in the same primary/licensed spectrum by exploiting the underlay spectrum sharing. To mitigate the secondary co-channel interference inflected at PUs, stringent secondary transmit power constraints are defined for the secondary access points (S-APs). A generalized pilots sharing scheme is used to locally estimate the uplink channels at P-APs/S-APs, and thereby, conjugate precoders are adopted to serve PUs/SUs in the same time-frequency resource element. Moreover, the effect of a user-centric AP clustering scheme is investigated by assigning a suitable set of APs to a particular user. The impact of estimated downlink (DL) channels at PUs/SUs via DL pilots beamformed by P-APs/S-APs is investigated. The achievable primary/secondary rates at PUs/SUs are derived for the statistical DL and estimated DL CSI cases. User-fairness for PUs/SUs is achieved by designing efficient transmit power control policies based on a multi-objective optimization problem formulation of joint underlay spectrum sharing and max-min criteria. The proposed orthogonal multiple-access based analytical framework is also extended to facilitate non-orthogonal multiple-access. Our analysis and numerical results manifest that the primary/secondary performance of underlay spectrum sharing can be boosted by virtue of the average reduction of transmit powers/path-losses, uniform coverage/service, and macro-diversity gains, which are inherent to distributed transmissions/receptions of cell-free massive MIMO.<br />Comment: 32 pages, 9 figures, Journal version
- Subjects :
- Signal Processing (eess.SP)
FOS: Computer and information sciences
Optimization problem
Computer science
business.industry
Computer Science - Information Theory
Information Theory (cs.IT)
MIMO
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
Interference (wave propagation)
Transmitter power output
Reduction (complexity)
Telecommunications link
FOS: Electrical engineering, electronic engineering, information engineering
Electrical Engineering and Systems Science - Signal Processing
Electrical and Electronic Engineering
Underlay
business
Power control
Computer network
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....2c00717c8cfb23224d261358431d790f
- Full Text :
- https://doi.org/10.48550/arxiv.2104.09671