Energy conservation is a critical problem in recently-emerging wireless sensor networks (WSNs). Pulse position modulation (PPM), as an exploring-worthy modulation format for energy efficiency, is tailored for WSNs...Energy conservation is a critical problem in recently-emerging wireless sensor networks (WSNs). Pulse position modulation (PPM), as an exploring-worthy modulation format for energy efficiency, is tailored for WSNs into two schemes, mono-mode PPM and multi-mode PPM, in this paper. Resorting to an idealized system model and a practical system model, which combine the power consumptions in transmission and reception modules of nodes with the idealized and real- istic battery characteristics, the battery energy efficiencies of mono-mode PPM and multi-mode PPM are evaluated and compared. To minimize the battery energy consumption (BEC), these schemes are further optimized in terms of constellation size M for a link in path-loss channels. Our analytical and numerical results show that considerable energy can be saved by multi-mode PPM; and the optimization performances of these schemes are noticeable at various communication distances though their optimization properties are different.展开更多
We study two instances of polynomial optimization problem over a single sphere. The first problem is to compute the best rank-1 tensor approximation. We show the equivalence between two recent semidefinite relaxations...We study two instances of polynomial optimization problem over a single sphere. The first problem is to compute the best rank-1 tensor approximation. We show the equivalence between two recent semidefinite relaxations methods. The other one arises from Bose-Einstein condensates(BEC), whose objective function is a summation of a probably nonconvex quadratic function and a quartic term. These two polynomial optimization problems are closely connected since the BEC problem can be viewed as a structured fourth-order best rank-1 tensor approximation. We show that the BEC problem is NP-hard and propose a semidefinite relaxation with both deterministic and randomized rounding procedures. Explicit approximation ratios for these rounding procedures are presented. The performance of these semidefinite relaxations are illustrated on a few preliminary numerical experiments.展开更多
基金the National Natural Science Foundation of China (Grant Nos. 60642007 and 10374051)the Scientific Fundation of Guangxi Education Department of China (Grant No. [2002]316)
文摘Energy conservation is a critical problem in recently-emerging wireless sensor networks (WSNs). Pulse position modulation (PPM), as an exploring-worthy modulation format for energy efficiency, is tailored for WSNs into two schemes, mono-mode PPM and multi-mode PPM, in this paper. Resorting to an idealized system model and a practical system model, which combine the power consumptions in transmission and reception modules of nodes with the idealized and real- istic battery characteristics, the battery energy efficiencies of mono-mode PPM and multi-mode PPM are evaluated and compared. To minimize the battery energy consumption (BEC), these schemes are further optimized in terms of constellation size M for a link in path-loss channels. Our analytical and numerical results show that considerable energy can be saved by multi-mode PPM; and the optimization performances of these schemes are noticeable at various communication distances though their optimization properties are different.
基金supported by National Natural Science Foundation of China (Grant Nos. 11401364, 11322109, 11331012, 11471325 and 11461161005)the National High Technology Research and Development Program of China (863 Program) (Grant No. 2013AA122902)+1 种基金the National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of SciencesNational Basic Research Program of China (973 Program) (Grant No. 2015CB856002)
文摘We study two instances of polynomial optimization problem over a single sphere. The first problem is to compute the best rank-1 tensor approximation. We show the equivalence between two recent semidefinite relaxations methods. The other one arises from Bose-Einstein condensates(BEC), whose objective function is a summation of a probably nonconvex quadratic function and a quartic term. These two polynomial optimization problems are closely connected since the BEC problem can be viewed as a structured fourth-order best rank-1 tensor approximation. We show that the BEC problem is NP-hard and propose a semidefinite relaxation with both deterministic and randomized rounding procedures. Explicit approximation ratios for these rounding procedures are presented. The performance of these semidefinite relaxations are illustrated on a few preliminary numerical experiments.