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Wireless network widely used today include, cellular network, wireless mesh network (WMNs), wireless local area network and personal area network. The increasing demand for these networks has turned spectrum into a precious resource. For this reason, there is always a need for methods to pack more bits/Hz. A particular solution is to use multiple antenna at both transmitter and receiver side. Such a system is called multiple-input multiple-output (MIMO) system. In real propagation environment of cellular communication, channel reuse will cause the co-channel interference which will degrade the MIMO channel performance. The interference cancellation (IC technology) can handle efficiently the cochannel interference. In this paper comparison computer simulation for zero forcing successive interference cancellation (ZF-SIC) minimum mean square error (MMSE equalizer) and maximum likelihood (ML) for two transmitting and two receiving antenna is shown.

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With the augmentation of High Performance Computing (HPC) system and power consumption pattern, energy optimization has become an important concern. Several surveys indicate that the energy utilized in computation and communication within a HPC system contributes considerably to their operational costs. The proposed energy efficient rescheduling algorithm aims to reduce energy consumption in HPC. This algorithm is based on energy efficient rescheduling of a job which considers the optimal operating point (OOP) i.e. voltage and frequency along with resource matching constraint to achieve the target performance. Performance -Energy-Time (PET) matrix for every application is built and stored in knowledge base (KB) in order to devise its OOP. The devised OOP gives minimal energy consumption at target execution environment. The algorithm is useful for energy optimization for cluster environment. Earlier works exploited process migration technique to address load balancing aspect. The proposed algorithm exploits process migration and reschedules the job dynamically with its OOP in context of energy reduction.

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