MFLP: a low power encoding for on chip networks

Network on chip (NoC) has been proposed as an appropriate solution for today’s on-chip communication challenges. Power dissipation has become a key factor in the NoCs because of their shrinking sizes. In this paper, we propose a new encoding approach aimed at power reduction by decreasing the number of switching activities on the buses. This approach assigns the symbols to data word in such a way that the more frequent words are sent by less power consumption. This algorithm dedicates the symbols with less ones to high probability data and uses transition signaling to transmit data. The proposed method, unlike the existing low power encoding, does not rely on spatial redundancy and keeps the width of the bus constant. Experimental evaluations show that our approach reduces the power dissipation up to 46 % with 2.70, 0.51, and 15.43 % power, critical path and area overhead in the NoCs, respectively.     

Multi-cell Optimal Downlink Beamforming Algorithm with Per-base Station Power Constraints

We consider a problem of optimizing multi-cell downlink throughput in multiple-input single-output (MISO) beamforming with single user per sub-channel in the wireless communication system. Previous work based on the generalization of uplink-downlink duality has already reformulated the maximum achievable downlink throughput into dual uplink throughput maximization problem. Since the dual uplink problem is nonconvex, it is difficult to find its optimal solution. The main contribution of this paper is a novel practical algorithm based on heuristic to find the solution of beamforer design satisfying the necessary optimality conditions of the dual uplink problem. Meanwhile the converged beamforming vectors can in turn improve the system sum rate significantly. As the dual problem is a mixed optimization, we also provide algorithms for its two sub-optimal problems. Simulation results validate the convergence and the efficiency of proposed algorithms.