1 research outputs found
Location Management in LTE Networks using Multi-Objective Particle Swarm Optimization
Long-term evolution (LTE) and LTE-advance (LTE-A) are widely used efficient
network technologies serving billions of users, since they are featured with
high spectrum efficiency, less latency, and higher bandwidth. Despite
remarkable advantages offered by these technologies, signaling overhead remains
a major issue in accessing the network. In particular, the load of signaling is
mainly attributed to location management. This paper proposes an efficient
approach for minimizing the total signaling overhead of location management in
LTE networks using multi-objective particle swarm optimization (MOPSO).
Tracking area update (TAU) and paging are considered to be the main elements of
the signaling overhead of optimal location management in LTE. In addition, the
total inter-list handover contributes significantly to the total signaling
overhead. However, the total signaling cost of TAU and paging is adversely
related to the total inter-list handover. Two cost functions should be
minimized, the first is the total signaling cost of TAU and paging and the
second is the total signaling overhead. The trade-off between these two
objectives can be circumvented by MOPSO, which alleviates the total signaling
overhead. A set of non-dominated solutions on the Pareto-optimal front is
defined and the best compromise solution. The proposed algorithm results
feasible compromise solution, minimizing the signaling overhead and the
consumption of the power battery of a user. The efficacy and the robustness of
the proposed algorithm have been proven using large scale environment problem
illustrative example. The location management in LTE networks using MOPSO best
compromise solution has been compared to a mixed integer non-linear programming
(MINLP) algorithm. Location management mobility management entity MME pooling
clustering SON Distributed Centralized pooling scheme fuzzy implementation
setup LP-CPLEXComment: Computer Network