Saturday 28 November 2015

Rank-Two Beamformed Secure Multicasting for Wireless Information and Power Transfer



SECURE MULTICASTING:

                       We investigate secure multicasting for simultaneous wireless information and power transfer (SWIPT) in the presence of multiple energy receivers who have potential to eavesdrop on the messages of information receivers.
Under both, signal-interference-noise ratio (SINR) and harvested energy constraints, we propose a novel secure multicast design to minimize the total power by using the techniques of rank-two beam formed Alamouti coding and semi definite relaxation (SDR).
 
                                              Fig: System and receiver model

The sufficient conditions are derived under which the proposed secure multicast design is optimal. We also present the corresponding rank-two Gaussian randomization procedure to obtain a suboptimal solution when SDR is not tight. Simulation results are then provided to demonstrate the efficacy of the proposed design in power saving.
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Friday 27 November 2015

Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks




Interferencealignment (IA) is a linear pre-coding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which could lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering that reduce CSI feedback overhead. 

We consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing.
 
First, there is a hidden partial CSI knowledge constraint in IA pre-coder design, which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing..
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