The power-saving class of type I (PSC I), which is one of the sleep-mode operations specified in the IEEE 802.16e standard, is designed to reduce power consumption for nonrealtime traffic. However, the inefficiency of the PSC I comes from the configuration of its operation and the utilized mechanism of binary-exponential traffic detection. Based on the concepts of IEEE 802.16m sleep-mode operation, a statistical sleep window control (SSWC) approach is proposed to improve the energy efficiency of a mobile station (MS) with nonreal-time downlink traffic in this paper. The SSWC approach constructs a discrete-time Markov-modulated Poisson process (dMMPP) for representing the states of nonreal-time traffic. Furthermore, a partially observable Markov decision process (POMDP) is exploited within the SSWC approach to conjecture the present traffic state. Based on the estimated traffic state and the considerations of tolerable delay and/or queue size, two suboptimal policies, including the sleep ratio-based (SR) and energy cost-based (EC) policies, are proposed within the SSWC approach. The efficiency of the proposed SSWC approach is evaluated and compared via simulations. Simulation results show that the proposed SSWC approach outperforms the conventional IEEE 802.16e PSC I and the evolutional PSC I of the IEEE 802.16m system in terms of both energy conservation and packet delay.

SUMMARYIn future wireless code division multiple access (WCDMA) cellular networks, random user mobility and time-varying multimedia traffic activity make the system design of coverage and capacity become a challenging issue. To utilise radio resource efficiently, it is crucial for cellular networks to have the capability of self-organisation for cell configuration, which can configure service coverage and system capacity dynamically to balance traffic loads among cells by being aware of the system situation. This paper proposes a reinforcement-learning-based self-organisation scheme for cell configuration in multimedia mobile networks, which takes into account both pilot power allocation and call admission control mechanisms. Simulation results show that the proposed scheme improves system performance significantly compared to the conventional fixed pilot power allocation scheme and the scheme in which only pilot power is adjusted dynamically but the criterion of the call admission control is not coupled to it.

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