Resource Allocation for Sum-Rate Maximization in Multi-UAV SCMA Networks

This work investigates a sparse code multiple access (SCMA) assisted multiple unmanned aerial vehicles (UAVs) downlink communication network for improved data services to multiple ground users. Our objective is to maximize the sum-rate of the multi-UAV SCMA network by optimizing the SCMA factor grap...

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Bibliographic Details
Published in2023 IEEE Globecom Workshops (GC Wkshps) pp. 1219 - 1224
Main Authors Chaturvedi, Saumya, Bohara, Vivek Ashok, Liu, Zilong, Srivastava, Anand, Xiao, Pei
Format Conference Proceeding
LanguageEnglish
Published IEEE 04.12.2023
Subjects
Autonomous aerial vehicles
Benchmark testing
Codes
Downlink
Factor Graph Matrix Assignment
Interference
Probabilistic LoS channel model
Resource management
Simulation
Sparse Code Multiple Access (SCMA)
Unmanned Aerial Vehicles (UAV) communications
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DOI10.1109/GCWkshps58843.2023.10464967

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Summary:This work investigates a sparse code multiple access (SCMA) assisted multiple unmanned aerial vehicles (UAVs) downlink communication network for improved data services to multiple ground users. Our objective is to maximize the sum-rate of the multi-UAV SCMA network by optimizing the SCMA factor graph matrix used for resource allocation, considering the inter-UAV and intra-UAV interference components. The formulated problem is non-convex in nature and is subject to the SCMA code-book constraints. We propose a factor graph matrix assignment algorithm to solve this optimization problem. Our simulation results demonstrate the superiority of the proposed scheme in terms of rate performance over the benchmark schemes. Thus, compared with orthogonal multiple access strategies, SCMA emerge as a promising candidate for next generation multiple access (NGMA) techniques.
DOI:10.1109/GCWkshps58843.2023.10464967