Self-optimisation of admission control and handover parameters in LTE

In mobile cellular networks the handover (HO) algorithm is responsible for determining when calls of users that are moving from one cell to another are handed over from the former to the latter. The admission control (AC) algorithm, which is the algorithm that decides whether new (fresh or HO) calls that enter a cell are allowed to the cell or not, often tries to facilitate HO by prioritising HO calls in favour of fresh calls. In this way, a good quality of service (QoS) for calls that are already admitted to the network is pursued. In this paper, the effect of self-optimisation of AC parameters on the HO performance in a long term evolution (LTE) network is studied, both with and without the self-optimisation of HO parameters. Simulation results show that the AC parameter optimisation algorithm considerably improves the HO performance by reducing the amount of calls that are dropped prior to or during HO

An enhanced weighted performance-based handover parameter optimization algorithm for LTE networks

This article introduces an enhanced version of previously developed self-optimizing algorithm that controls the handover (HO) parameters of a long-term evolution base station in order to diminish and prevent the negative effects that can be introduced by HO (radio link failures, HO failures and ping-pong HOs) and thus improve the overall network performance. The default algorithm selects the best hysteresis and time-to-trigger combination based on the current network status. The enhancement proposed here aims to maximize the gain provided by the algorithm by improving its convergence time. The effects of this enhancement have been studied in a rural scenario setting and compared to the original algorithm; the results show a clear improvement, faster convergence, and better network performance, because of the enhancement

Modelling the time-varying cell capacity in LTE networks

In wireless orthogonal frequency-division multiple access (OFDMA) based networks like Long Term Evolution (LTE) or Worldwide Interoperability for Microwave Access (WiMAX) a technique called adaptive modulation and coding (AMC) is applied. With AMC, different modulation and coding schemes (MCSs) are used to serve different users in order to maximise the throughput and range. The used MCS depends on the quality of the radio link between the base station and the user. Data is sent towards users with a good radio link with a high MCS in order to utilise the radio resources more efficiently while a low MCS is used for users with a bad radio link. Using AMC however has an impact on the cell capacity as the quality of a radio link varies when users move around; this can even lead to situations where the cell capacity drops to a point where there are too little radio resources to serve all users. AMC and the resulting varying cell capacity notably has an influence on admission control (AC). AC is the algorithm that decides whether new sessions are allowed to a cell or not and bases its decisions on, amongst others, the cell capacity. The analytical model that is developed in this paper models a cell with varying capacity caused by user mobility using a continuous -time Markov chain (CTMC). The cell is divided into multiple zones, each corresponding to the area in which data is sent towards users using a certain MCS and transitions of users between these zones are considered. The accuracy of the analytical model is verified by comparing the results obtained with it to results obtained from simulations that model the user mobility more realistically. This comparison shows that the analytical model models the varying cell capacity very accurately; only under extreme conditions differences between the results are noticed. The developed analytical and simulation models are then used to investigate the effects of a varying cell capacity on AC. Also, an optimisation algorithm that adapts the parameter of the AC algorithm which determines the amount of resources that are reserved in order to mitigate the effects of the varying cell capacity is studied using the models. Updating the parameter of the AC algorithm is done by reacting to certain triggers that indicate good or bad performance and adapt the parameters of the AC algorithm accordingly. Results show that using this optimisation algorithm improves the quality of service (QoS) that is experienced by the users.This work was partially supported by the Spanish Government through project TIN2010-21378-C02-02 and contract BES-2007-15030.Sas, B.; Bernal Mor, E.; Spaey, K.; Pla, V.; Blondia, C.; Martínez Bauset, J. (2014). Modelling the time-varying cell capacity in LTE networks. 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Analysis of the Influence of Video-Aware Traffic Management on the Performance of the Dejittering Mechanism ⋆

Abstract. IPTV over DSL access networks is becoming a reality. This paper studies the impact of the presence of a video-aware traffic management module in the access network on the performance of the video dejittering mechanism at the receiver. The presented numerical results illustrate that with the traffic management module, the packet loss probability at the dejittering buffer decreases. Since the traffic management module will only drop the least important enhancement layer packets of the video in case of congestion, especially the important base layer packets of the video gain from the use of the traffic management module. All results in this paper are obtained using a mathematical model.