Distributed caching for data dissemination in the downlink of heterogeneous networks
Distributed caching for data dissemination in the downlink of heterogeneous networks
Heterogeneous cellular networks (HCN) with embedded small cells are considered, where multiple mobile users wish to download network content of different popularity. By caching data into the small-cell base stations (SBS), we will design distributed caching optimization algorithms via belief propagation (BP) for minimizing the downloading latency. First, we derive the delay-minimization objective function (OF) and formulate an optimization problem. Then we develop a framework for modeling the underlying HCN topology with the aid of a factor graph. Furthermore, distributed BP algorithm is proposed based on the network’s factor graph. Next, we prove that a fixed point of convergence exists for our distributed BP algorithm. In order to reduce the complexity of the BP, we propose a heuristic BP algorithm. Furthermore, we evaluate the average downloading performance of our HCN for different numbers and locations of the base stations (BS) and mobile users (MU), with the aid of stochastic geometry theory. By modeling the nodes distributions using a Poisson point process, we develop the expressions of the average factor graph degree distribution, as well as an upper bound of the outage probability for random caching schemes. We also improve the performance of random caching. Our simulations show that (1) the proposed distributed BP algorithm has a near-optimal delay performance, approaching that of the highcomplexity exhaustive search method, (2) the modified BP offers a good delay performance at a low communication complexity, (3) both the average degree distribution and the outage upper bound analysis relying on stochastic geometry match well with our Monte-Carlo simulations, and (4) the optimization based on the upper bound provides both a better outage and a better delay performance than the benchmarks.
heterogeneous cellular networks, wireless caching, belief propagation, stochastic geometry
3553-3568
Li, Jun
173328aa-1759-4a78-9514-319c5a6ff4b0
Chen, Youjia
9daeaa05-b641-476a-883f-fa92da02b000
Lin, Zihuai
ccf46fdb-cda4-4fbe-9cab-41ba727def88
Chen, Wen
cd79c830-db68-43c5-9b32-3f47be6bc956
Vucetic, Branka
46b48899-92c1-4fa9-91ab-b6f6a2c7cb83
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
October 2015
Li, Jun
173328aa-1759-4a78-9514-319c5a6ff4b0
Chen, Youjia
9daeaa05-b641-476a-883f-fa92da02b000
Lin, Zihuai
ccf46fdb-cda4-4fbe-9cab-41ba727def88
Chen, Wen
cd79c830-db68-43c5-9b32-3f47be6bc956
Vucetic, Branka
46b48899-92c1-4fa9-91ab-b6f6a2c7cb83
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Li, Jun, Chen, Youjia, Lin, Zihuai, Chen, Wen, Vucetic, Branka and Hanzo, Lajos
(2015)
Distributed caching for data dissemination in the downlink of heterogeneous networks.
IEEE Transactions on Communications, 63 (10), .
(doi:10.1109/TCOMM.2015.2455500).
Abstract
Heterogeneous cellular networks (HCN) with embedded small cells are considered, where multiple mobile users wish to download network content of different popularity. By caching data into the small-cell base stations (SBS), we will design distributed caching optimization algorithms via belief propagation (BP) for minimizing the downloading latency. First, we derive the delay-minimization objective function (OF) and formulate an optimization problem. Then we develop a framework for modeling the underlying HCN topology with the aid of a factor graph. Furthermore, distributed BP algorithm is proposed based on the network’s factor graph. Next, we prove that a fixed point of convergence exists for our distributed BP algorithm. In order to reduce the complexity of the BP, we propose a heuristic BP algorithm. Furthermore, we evaluate the average downloading performance of our HCN for different numbers and locations of the base stations (BS) and mobile users (MU), with the aid of stochastic geometry theory. By modeling the nodes distributions using a Poisson point process, we develop the expressions of the average factor graph degree distribution, as well as an upper bound of the outage probability for random caching schemes. We also improve the performance of random caching. Our simulations show that (1) the proposed distributed BP algorithm has a near-optimal delay performance, approaching that of the highcomplexity exhaustive search method, (2) the modified BP offers a good delay performance at a low communication complexity, (3) both the average degree distribution and the outage upper bound analysis relying on stochastic geometry match well with our Monte-Carlo simulations, and (4) the optimization based on the upper bound provides both a better outage and a better delay performance than the benchmarks.
Text
tcomm-hanzo-2455500-proof.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 7 July 2015
e-pub ahead of print date: 13 July 2015
Published date: October 2015
Keywords:
heterogeneous cellular networks, wireless caching, belief propagation, stochastic geometry
Identifiers
Local EPrints ID: 381888
URI: http://eprints.soton.ac.uk/id/eprint/381888
PURE UUID: 257fdce7-fc2b-4f7c-b42b-bfcdf55385c5
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Date deposited: 14 Oct 2015 14:26
Last modified: 18 Mar 2024 02:35
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Contributors
Author:
Jun Li
Author:
Youjia Chen
Author:
Zihuai Lin
Author:
Wen Chen
Author:
Branka Vucetic
Author:
Lajos Hanzo
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