This paper is concerned with distributed estimation of a scalar parameter using a wireless sensor network (WSN) that\nemploys a large number of sensors operating under limited bandwidth resource. A semi-orthogonal multiple-access\n(MA) scheme is proposed to transmit observations from K sensors to a fusion center (FC) via N orthogonal channels,\nwhere K � N. The K sensors are divided into N groups, where the sensors in each group simultaneously transmit on\none orthogonal channel (and hence the transmitted signals are directly superimposed at the FC as opposed to be\ncoherently combined). Under such a semi-orthogonal multiple access channel (MAC), performance of the linear\nminimum mean squared error (LMMSE) estimation is analyzed in terms of two indicators: the channel noise\nsuppression capability and the observation noise suppression capability. The analysis is performed for two versions of\nthe proposed semi-orthogonal MA scheme: fixed sensor grouping and adaptive sensor grouping. In particular, the\nsemi-orthogonal MAC with fixed sensor grouping is shown to have the same channel noise suppression capability\nand two times the observation noise suppression capability when compared to the orthogonal MAC under the same\nbandwidth resource. For the semi-orthogonal MAC with adaptive sensor grouping, it is determined that N = 4 is the\nmost favorable number of orthogonal channels when taking into account both performance and feedback\nrequirement. In particular, the semi-orthogonal MAC with adaptive sensor grouping is shown to perform very close to\nthat of the hybrid MAC, while requiring only log2 N = 2 bits of information feedback instead of the exact channel\nphase for each sensor.
Loading....