TY - GEN
T1 - Neighbor discovery in wireless networks using compressed sensing with Reed-Muller codes
AU - Zhang, Lei
AU - Guo, Dongning
PY - 2011
Y1 - 2011
N2 - A novel scheme for full-duplex neighbor discovery in wireless networks is proposed. The scheme allows all nodes to simultaneously discover one-hop neighbors and identify their network interface addresses (NIAs) within a single frame of transmission, which typically consists of no more than a few thousand symbols. The key technique is to assign each node a unique on-off signature derived from a second-order Reed-Muller code and let all nodes simultaneously transmit their signatures. Despite that the radio is half-duplex, each node observes a superposition of its neighbors' signatures (partially) through its own off-slots. To identify its (small number of) neighbors out of a large network address space, each node solves a compressed sensing (or sparse recovery) problem using a chirp reconstruction algorithm. A network of over one million Poisson distributed nodes (with 20-bit NIAs) is studied numerically, where each node has 30 neighbors on average, and the channel between each pair of nodes is subject to path loss and Rayleigh fading. Within a single frame of 4,096 symbols, nodes can discover their respective neighbors with on average 99.9% accuracy at 16 dB signal-to-noise ratio (SNR). The algorithm is scalable to networks of virtually any size of practical interest due to its sub-linear complexity. The new scheme requires much fewer transmissions than conventional random-access discovery schemes to achieve the same performance.
AB - A novel scheme for full-duplex neighbor discovery in wireless networks is proposed. The scheme allows all nodes to simultaneously discover one-hop neighbors and identify their network interface addresses (NIAs) within a single frame of transmission, which typically consists of no more than a few thousand symbols. The key technique is to assign each node a unique on-off signature derived from a second-order Reed-Muller code and let all nodes simultaneously transmit their signatures. Despite that the radio is half-duplex, each node observes a superposition of its neighbors' signatures (partially) through its own off-slots. To identify its (small number of) neighbors out of a large network address space, each node solves a compressed sensing (or sparse recovery) problem using a chirp reconstruction algorithm. A network of over one million Poisson distributed nodes (with 20-bit NIAs) is studied numerically, where each node has 30 neighbors on average, and the channel between each pair of nodes is subject to path loss and Rayleigh fading. Within a single frame of 4,096 symbols, nodes can discover their respective neighbors with on average 99.9% accuracy at 16 dB signal-to-noise ratio (SNR). The algorithm is scalable to networks of virtually any size of practical interest due to its sub-linear complexity. The new scheme requires much fewer transmissions than conventional random-access discovery schemes to achieve the same performance.
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U2 - 10.1109/WIOPT.2011.5930008
DO - 10.1109/WIOPT.2011.5930008
M3 - Conference contribution
AN - SCOPUS:79960617391
SN - 9781612848242
T3 - 2011 International Symposium on Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks, WiOpt 2011
SP - 154
EP - 160
BT - 2011 International Symposium on Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks, WiOpt 2011
T2 - 2011 International Symposium of on Modeling and Optimization of Mobile, Ad Hoc, and Wireless Networks, WiOpt 2011
Y2 - 9 May 2011 through 13 May 2011
ER -