Dynamic Tracking Area List configuration and performance evaluation in LTE

Razavi, Sara Modarres; Yuan, Di; Gunnarsson, Fredrik; Moe, Johan

doi:10.1109/glocomw.2010.5700370

Cited by 33 publications

(39 citation statements)

References 10 publications

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“…Clearly, imposing assumptions on UE behavior, ranging from simple rules of thumb to statistical mobility models of UE trajectory, constrains the applicability of TAL optimization. Nevertheless, previous works, in particular [16,17], show TAL is promising in extending the capability of the conventional TA concept.…”

Section: Related Workmentioning

confidence: 99%

“…Previous studies of using TAL for minimizing the overall signaling overhead, with the assumption that a cell gives one common TAL to all UEs getting updated in the cell, have been presented in [8,16,17]. TALs, in forms of rings of cells, are used in [8].…”

Section: Related Workmentioning

confidence: 99%

“…TALs, in forms of rings of cells, are used in [8]. In [16,17], each cell has a cell-specific TAL to be assigned to all users registered or updated in the cell. To optimize the composition and use of TALs, one has to take into account the fact that, in general, UEs in the same location may hold different TALs, in contrast to the conventional TA case.…”

Section: Related Workmentioning

confidence: 99%

“…The flexibility in forming TAs is related to the sizes of its building elements (i.e., TAs). The most flexible setting is that each cell (or site) is considered a TA, and the effect of larger TAs is implemented by TALs [8,16,17]. For reducing TAU, this setting is not necessary, as overlapping TALs can be created and applied to any given TA layout in order to yield a "blurring effect" of the TA boundaries, with the effect of smearing the TAUs over a larger area.…”

mentioning

confidence: 99%

“…Thus, it is hard to calculate or estimate the performance of candidate TAL configurations in advance. One approach for circumventing the issue is to use mobility models [8,16,17]. However, the performance is highly sensitive to the validity of the assumptions made in the models.…”

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confidence: 99%

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Mitigating signaling congestion in LTE location management by overlapping tracking area lists

Razavi

Yuan

2012

Computer Communications

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Avoiding signaling congestion is a key aspect in location management of cellular networks. The signaling load in this context corresponds to the use of location update and paging messages for tacking user equipments (UEs).Signaling congestion may occur due to many UEs behaving in a similar manner, e.g., massive and simultaneous UE mobility in a train movement scenario. For Long Term Evolution (LTE) networks, location management can be based on the use of tracking area lists (TALs), each being a list containing multiple tracking areas (TAs). In this paper, the scheme of using TALs with overlapping TAs is applied for signaling congestion mitigation. One or multiple TALs that potentially overlap are allocated to each cell, and the TALs are assigned to the UEs that make their location updates in the cell. We derive linear programming formulations for finding the optimal proportional use of overlapping TALs for congestion avoidance. The main advantage of our approach is that it does not require the collection of detailed UE mobility information apart from what is available to the network. We report numerical results for realistic scenarios. The optimization approach yields * Corresponding author. Preprint submitted to Computer Communications JournalAugust 6, 2012promising results for reducing signaling congestion, and the performance region of optimized overlapping TALs goes significantly beyond the capability of the conventional TA scheme.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Mitigating signaling congestion in LTE location management by overlapping tracking area lists

Razavi

Yuan

2012

Computer Communications

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Optimal location management in LTE networks using evolutionary techniques

Aqeeli

Hashim

Haque

et al. 2019

Int J Communication

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Summary Wireless network is considered a vital enabler in the world of information technology, specifically, LTE and LTE advanced networks, which are the latest technologies owing to their fast speed, robustness, and large bandwidth. However, in spite of the aforementioned advancements, signaling overhead poses critical challenges in terms of network availability, especially those caused by location management messages which are related to users’ mobility behavior. This paper seeks to address the problem of signaling overhead caused by the location management messages specifically, tracking area update (TAU) and paging by deploying three evolutionary algorithms, namely particle swarm optimization (PSO), artificial bee colony (ABC), and gravitational search algorithm (GSA). The deployed algorithms guarantee yielding the minimum values of the signaling overhead for TAU, paging, and the battery power consumption of the user. It is shown that ABC‐based algorithm has faster convergence and better signaling overhead when compared with other implemented algorithms. Moreover, the measured relative standard deviation (RSD) value of all algorithms shows low uncertainty of around 1% for the objective function and 3% for the paging, TAU, and power. Hence, the three applied optimization algorithms have proven to be efficient and reliable for solving the problem in a large‐scale environment.

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