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Analysis and Optimization of Random Caching in Multi-Antenna Small-Cell Networks With Limited Backhaul
- Source :
- IEEE Transactions on Vehicular Technology. 68:7789-7803
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Caching at base station is a promising technology to reduce the backhaul loads in future wireless networks. To exploit the content diversity gain and multiple antenna transmission, in this paper, we consider the analysis and optimization of random caching in multi-antenna small-cell networks with limited backhaul. We analyze the performance of the success probability, which is defined as the probability that the requested file is not only obtained from the cache or the backhaul at the small base station (SBS), but also successfully delivered via the wireless link from the SBS to the user. Using tools from stochastic geometry, we first derive an exact expression and an upper bound of the success probability. Based on the analytical results, we then consider network throughput maximization by optimizing the design parameters in the cache-enabled multi-antenna small-cell networks. The optimization problem is a complicated mixed-integer optimization problem. After analyzing the optimal properties, we obtain a local optimal solution with low complexity. To further simplify the optimization, we solve an asymptotic optimization problem in the high user density region, using the upper bound as the objective function. Numerical simulations show that our proposed scheme improves the performance by up to $14\%$ when the Zipf parameter is 0.4 and the antenna number is 8.
- Subjects :
- Mathematical optimization
Optimization problem
Computer Networks and Communications
Computer science
Wireless network
business.industry
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
Aerospace Engineering
Throughput
Upper and lower bounds
Backhaul (telecommunications)
Base station
Diversity gain
Automotive Engineering
Wireless
Cache
Small cell
Electrical and Electronic Engineering
business
Subjects
Details
- ISSN :
- 19399359 and 00189545
- Volume :
- 68
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Vehicular Technology
- Accession number :
- edsair.doi...........453184f765b3fcfb4451c39d38624725
- Full Text :
- https://doi.org/10.1109/tvt.2019.2924642