Cache Content Placement Optimization in Non-Orthogonal Multiple Access Networks

Incorporating wireless caching in non-orthogonal multiple access (NOMA) networks is a promising technique to reduce the delivery latency and improve the quality of service. In this paper, we study a cache content placement optimization problem in a cellular NOMA downlink wireless caching network. Ou...

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Vydáno v:IEEE transactions on communications Ročník 68; číslo 7; s. 4580 - 4591
Hlavní autoři: Li, Yiqing, Jiang, Miao, Zhang, Qi, Qin, Jiayin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Cache content placement optimization
Caching
Communication system security
Computer simulation
constrained concave-convex procedure (CCCP)
Constraints
Delays
Integer programming
Iterative methods
Knapsack problem
Network latency
NOMA
non-linear integer programming (NLIP)
non-orthogonal multiple access (NOMA)
Nonorthogonal multiple access
Optimization
Placement
Polynomials
quadratic knapsack problem (QKP)
Resource management
Wireless communication
Wireless networks
Wireless sensor networks
ISSN:0090-6778, 1558-0857
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Shrnutí:Incorporating wireless caching in non-orthogonal multiple access (NOMA) networks is a promising technique to reduce the delivery latency and improve the quality of service. In this paper, we study a cache content placement optimization problem in a cellular NOMA downlink wireless caching network. Our goal is to minimize the average transmit power under the cache capacity constraints. The optimization problem is a non-linear integer programming, which is non-deterministic polynomial-time hard. To efficiently solve the problem, an alternating upper plane method based on quadratic knapsack problem (QKP) is proposed. To deal with the general situation that the sizes of files and cache capacities are not integers, an alternating method based on semidefinite relaxation is also proposed. Finally, a constrained concave-convex procedure-based iterative method is proposed to further reduce the computational complexity. Simulation results show that our proposed methods are superior to the schemes which cache the most popular files until the cache is full.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2020.2985958