2007
DOI: 10.1049/iet-com:20050496
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Optimality properties and performance analysis of co-operative time-reversal communication in wireless sensor networks

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Cited by 14 publications
(4 citation statements)
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“…These in turn are dependent upon the number of data samples gathered for estimation, the quantization level used to digitize the data samples, and the signal-to-noise ratio (SNR) of the received training signal. The performance of a TR system with a sampling rate above the Nyquist rate, very fine quantization steps, and very high training signal SNR (that is, essentially perfect TR) will approach the theoretically optimal peak output SNR predicted for the forward (non-training) channel [2]; however, this comes at the cost of significant overhead in terms of computational resources. Furthermore, even with a sufficiently high sampling rate and quantization level, retransmission of a noisy version of the timereversed training signal can cause significant performance degradation.…”
Section: Introductionmentioning
confidence: 99%
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“…These in turn are dependent upon the number of data samples gathered for estimation, the quantization level used to digitize the data samples, and the signal-to-noise ratio (SNR) of the received training signal. The performance of a TR system with a sampling rate above the Nyquist rate, very fine quantization steps, and very high training signal SNR (that is, essentially perfect TR) will approach the theoretically optimal peak output SNR predicted for the forward (non-training) channel [2]; however, this comes at the cost of significant overhead in terms of computational resources. Furthermore, even with a sufficiently high sampling rate and quantization level, retransmission of a noisy version of the timereversed training signal can cause significant performance degradation.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, even with a sufficiently high sampling rate and quantization level, retransmission of a noisy version of the timereversed training signal can cause significant performance degradation. One approach to reducing the computational complexity as well as introducing some possible robustness to training signal distortion is to utilize so-called one-bit time-reversal, in which only two quantization levels are required [2][3][4][5][6][7]. This method has been shown to significantly reduce the system complexity but a significant amount of information is lost due to one bit quantization.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, many trials adopt the UWB radio system to a wireless sensor network, which is considered as one of the main applications of the 802. 15.4a standard [4,5]. Recently, UWB radio communication has also been considered as one of the physical layer candidates for IEEE 802.…”
Section: Introductionmentioning
confidence: 99%
“…(a) n sink nodes transmit a short sequence of Ultra-Wideband training pulses to m network nodes, (b) m network nodes transmit time reversal signal to n sink nodes.Let us consider the basic principles of MIMO WSN based on TR technology inFig.1[3]. Define ( ) mn h t the channel impulse response (CIR) relating the m-th node to the n-th sink node.…”
mentioning
confidence: 99%