Broadband wireless serves as one of the most significant communication technologies in our information era. As the community urges for higher capability and larger coverage of networking system to support various applications such as data sharing and multimedia, more research works are dedicated in order to provide a solution for building a more reliable and robust system. Moving from stationary to supporting mobility and portability, designing of an efficient power management is an immediate issue. We are called to develop a better mechanism to minimize the power consumption and provide with sufficient Quality of Service (QoS) at the same time....[ Read more ]

Broadband wireless serves as one of the most significant communication technologies in our information era. As the community urges for higher capability and larger coverage of networking system to support various applications such as data sharing and multimedia, more research works are dedicated in order to provide a solution for building a more reliable and robust system. Moving from stationary to supporting mobility and portability, designing of an efficient power management is an immediate issue. We are called to develop a better mechanism to minimize the power consumption and provide with sufficient Quality of Service (QoS) at the same time.

To realize our goal, the IEEE 802.16e-2005 (Mobile Broadband Wireless Access) standard provides a mobility version of WiMAX which is enhanced with power-saving features in the Medium Access Control (MAC) layer to prolong the battery lifetime of a mobile station. In a previous study, an accurate model of Power Saving Classes (PSCs) was proposed using embedded Markov Chain analysis. This study was investigated using a simple static timeout scheme to derive the evaluation of system performance. Later a novel system framework and was formulated based on the Markov Decision Process (MDP) to determine the optimal selection between different PSCs. This optimization problem was solved using a proposed Policy Optimization (PO) algorithm. However, no comparative study has been done based on these two different schemes. The actual performance is crucial to the system analysis as we proceed further in the implementation. Thus, we implement these two schemes separately and simulate using a well-known network simulator ns-2 to compare them and demonstrate their differences. We highlight the energy consumption and delay tradeoff between these two different schemes. In addition, a traffic rate estimator has been added to the PO algorithm to finalize the runtime implementation. In addition, frequent switching over the idle time period is an issue in the MDP approach although the optimal performance can be achieved in a long run. With the help of PO algorithm, we propose a novel joint scheme with the optimal timeout value for the system to decide when to sleep and how to sleep to achieve the same performance as the PO algorithm but with less switching frequency. Finally, we give a conclusion about our previous research work.

On the other hand, most of the existing works on the IEEE 802.16e sleep mode operation focus on the decision making before a mobile station switching to sleep mode state. The correlation of the decision is mainly on when and how to sleep based on the traffic demands. After the mobile station is switched to sleep mode, the deactivation of it mainly depends on new incoming traffic regardless of the actual amount. Truly, frequent switching can increase the energy cost on the mobile station, which can significantly reduce the battery lifetime. To minimize the switching frequency, we propose a novel approach to resolve this issue by making a heuristic decision during the listening interval. With this aim, we propose a real-time heuristic algorithm, WAKSLP_DECISION, to accommodate our target. Three main decision criteria are analyzed and designed, namely the probability of buffer overflow, expected delay violation, and battery lifetime expiry, to achieve our goal. We verify the energy consumption performance with simulation experiments to validate our proposed scheme. The result shows that our scheme performs 25% to 30% better compared with the original standard in terms of energy consumption. We believe this algorithm is practical and implementable with only a slight modification to the original standard, which can contribute both in the research community and industrial development.

Finally, we outline some open issues based on our research work. We strongly believe that our investigation can bring a different perspective to contribute to our research community with a theoretical approach and practical implementation in the energy-efficient design on mobile wireless broadband access systems.