Reducing Location Update and Paging Cost in a PCS Network

Author(s):  
Pablo Garcia Escalle ◽  
Vicente Casares Giner ◽  
Jorge Mataix Oltra
Keyword(s):  
Author(s):  
I.S. Misra ◽  
M.K.S. Mahapatra ◽  
S. Karmakar ◽  
P.S. Bhattacharjee ◽  
D. Saha ◽  
...  

2013 ◽  
Vol 32 (8) ◽  
pp. 2090-2094
Author(s):  
Long CHEN ◽  
Hong-bo TANG ◽  
Ling-wei WANG

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7336
Author(s):  
Mincheol Paik ◽  
Haneul Ko

Frequent location updates of individual Internet of Things (IoT) devices can cause several problems (e.g., signaling overhead in networks and energy depletion of IoT devices) in massive machine type communication (mMTC) systems. To alleviate these problems, we design a distributed group location update algorithm (DGLU) in which geographically proximate IoT devices determine whether to conduct the location update in a distributed manner. To maximize the accuracy of the locations of IoT devices while maintaining a sufficiently small energy outage probability, we formulate a constrained stochastic game model. We then introduce a best response dynamics-based algorithm to obtain a multi-policy constrained Nash equilibrium. From the evaluation results, it is demonstrated that DGLU can achieve an accuracy of location information that is comparable with that of the individual location update scheme, with a sufficiently small energy outage probability.


Author(s):  
Swati Swayamsiddha ◽  
Chetna Singhal ◽  
Rajarshi Roy

Nature-Inspired algorithms have gained relevance particularly for solving complex optimization problems in engineering domain. An overview of implementation modeling of the established algorithms to newly developed algorithms is outlined. Mobile location management has vital importance in wireless cellular communication and can be viewed as an optimization problem. It has two aspects: location update and paging where the objective is to reduce the overall cost incurred corresponding to these two operations. The potential application of the Nature-Inspired algorithms to mobile location management is studied. Many such algorithms are recently being explored along with incremental modifications to the existing techniques. Finally, analysis and insights highlight the further scopes of the Nature-Inspired algorithms to mobile location management application.


Author(s):  
Smita Parija ◽  
Sudhansu Sekhar Singh ◽  
Swati Swayamsiddha

Location management is a very critical and intricate problem in wireless mobile communication which involves tracking the movement of the mobile users in the cellular network. Particle Swarm Optimization (PSO) is proposed for the optimal design of the cellular network using reporting cell planning (RCP) strategy. In this state-of-the-art approach, the proposed algorithm reduces the involved total cost such as location update and paging cost for the location management issue. The same technique is proved to be a competitive approach to different existing test network problems showing the efficacy of the proposed method through simulation results. The result obtained is also validated for real network data obtained from BSNL, Odisha. Particle Swarm Optimization is used to find the optimal set of reporting cells in a given cellular network by minimizing the location management cost. This RCP technique applied to this cost minimization problem has given improved result as compared to the results obtained in the previous literature.


Author(s):  
Lai Tu ◽  
Furong Wang ◽  
Fan Zhang ◽  
Jian Zhang

2009 ◽  
pp. 650-681
Author(s):  
Samuel Pierre

This chapter analyzes and proposes some mobility management models and schemes by taking into account their capability to reduce search and location update costs in wireless mobile networks. The first model proposed is called the built-in memory model; it is based on the architecture of the IS-41 network and aims at reducing the home-location-register (HLR) access overhead. The performance of this model was investigated by comparing it with the IS-41 scheme for different call-to-mobility ratios (CMRs). Experimental results indicate that the proposed model is potentially beneficial for large classes of users and can yield substantial reductions in total user-location management costs, particularly for users who have a low CMR. These results also show that the cost reduction obtained on the location update is very significant while the extra costs paid to locate a mobile unit simply amount to the costs of crossing a single pointer between two location areas. The built-in memory model is also compared with the forwarding pointers’ scheme. The results show that this model consistently outperforms the forwarding pointers’ strategy. A second location management model to manage mobility in wireless communications systems is also proposed. The results show that significant cost savings can be obtained compared with the IS-41 standard location-management scheme depending on the value of the mobile units’ CMR.


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