The aim of this paper is to evaluate how Discontinuous Reception (DRX) cycles and related timers take effect to Voice over IP (VoIP) performance when High Speed Downlink Packet Access (HSDPA) networks are in question. DRX cycles limit the scheduling freedom of users and increase battery saving opportunities in the User Equipment (UE) by allowing it to turn its receiver circuitry off for some periods of time. Prior work has concentrated mainly on optimizing the usage of radio resources when small bit rate delay critical services, like VoIP, are considered. However, the battery life of small handheld devices might become a limiting factor in providing satisfactory user experience. Thus, this paper evaluates the performance also from the battery life perspective when DRX cycles together with VoIP are considered. The performance is evaluated with a fully dynamic system level tool in which the mobility of the users, radio resource management functionalities and the interactions between them are explicitly taken into account. The study indicated that the longer the DRX cycle is the higher are the battery saving opportunities but at the same time VoIP over HSDPA capacity can be compromised. Capacity degeneration in pure VoIP traffic simulations was, however, possible to be mitigated by using an adequately long inactivity timer. In mixed traffic scenarios including both VoIP and Best Effort (BE) traffic, higher cell throughput was achieved by allowing more scheduling time for BE users with adequately long DRX cycle and a short inactivity timer.

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3GPP has specified that terminals can be configured to use either 2 or 10 ms transmission time interval in high speed uplink packet access systems. The purpose of this paper is to evaluate the benefit of exploiting a mixture of both of the transmissions time intervals within a cell instead of only one. The study is quantified by means of studying the achievable coverage of voice over IP and possible battery saving benefits. The analysis is conducted with a system level simulator modeling network and terminal behavior in detail. The paper indicates that utilizing a mixture of both transmission time intervals can extend coverage whilst providing enhanced battery saving opportunities.

This paper introduces a framework and implementation of a cognitive self-healing system for fault detection and compensation in future mobile networks. Performance monitoring for failure identification is based on anomaly analysis, which is a combination of the nearest neighbor anomaly scoring and statistical profiling. Case-based reasoning algorithm is used for cognitive self-healing of the detected faulty cells. Validation environment is Long Term Evolution (LTE) mobile system simulated with Network Simulator 3 (ns-3) [1,2]. Results demonstrate that cognitive approach is efficient for compensation of cell outages and is capable to improve network coverage. Anomaly analysis can be used for identification of network failures, and automation of performance management. Introduction of data mining and cognition to the future mobile networks, e.g. 5 th Generation (5G), is especially important as it allows to meet the strict requirements for robustness and enhanced performance.

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