Browsing by Author "Maunder, Robert G."

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Fusion-Based Cooperative Support Identification for Compressive Networked Sensing
(2020-02-01)
Yang, Ming-Hsun
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Wu, Jwo-Yuh
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Wang, Tsang-Yi
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Maunder, Robert G.
;
Gau, Rung-Hung
This letter proposes a fusion-based cooperative support identification scheme for distributed compressive sparse signal recovery via resource-constrained wireless sensor networks. The proposed support identification protocol involves: (i) local sparse sensing for economizing data gathering and storage, (ii) local binary decision making for partial support knowledge inference, (iii) binary information exchange among active nodes, and (iv) binary data aggregation for support estimation. Then, with the aid of the estimated signal support, a refined local decision is made at each node. Only the measurements of those informative nodes will be sent to the fusion center, which employs a weighted l(1)-minimization for global signal reconstruction. The design of a Bayesian local decision rule is discussed, and the average communication cost is analyzed. Computer simulations are used to illustrate the effectiveness of the proposed scheme.
Low-Latency Compressive Active User Identification over Frequency-Selective Fading Channels
(2018-01-01)
Chang, Chun-Yi
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Wu, Jwo-Yuh
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Yang, Ming-Hsun
;
Wang, Tsang-Yi
;
Shao, Shuai
This paper proposes a compressive sensing (CS) based active user identification scheme over frequency-selective fading channels. Unlike the conventional cyclic prefix (CP) based preamble transmission, our approach does not utilize CP in order to conserve signaling overhead, in turn reducing the system-wide processing latency. Our approach first estimates the multi-user channel impulse response vectors by solving a mixed l(2 )/ l(1) - norm optimization problem; then, the active users are identified via a sorting of the norms of the estimated channel vectors. By exploiting the Toeplitz channel matrix structure resulting from CP-free preamble transmission, analytic performance guarantee in term of the block restricted isometry property of the preamble matrix is given. Computer simulations are used to illustrate the performance of the proposed method.
Survey of Turbo, LDPC, and Polar Decoder ASIC Implementations
(2019-01-01)
Shao, Shuai
;
Hailes, Peter
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Wang, Tsang-Yi
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Wu, Jwo-Yuh
;
Maunder, Robert G.
Channel coding may be viewed as the best-informed and most potent component of cellular communication systems, which is used for correcting the transmission errors inflicted by noise, interference, and fading. The powerful turbo code was selected to provide channel coding for mobile broad band data in the 3G UMTS and 4G long term evolution cellular systems. However, the 3GPP standardization group has recently debated whether it should be replaced by low density parity check (LDPC) or polar codes in 5G new radio, ultimately reaching the decision to adopt the LDPC code family for enhanced mobile broad band (eMBB) data and polar codes for eMBB control. This paper summarizes the factors that influenced this debate, with a particular focus on the application specific integrated circuit (ASIC) implementation of the decoders of these three codes. We show that the overall implementation complexity of turbo, LDPC, and polar decoders depends on numerous other factors beyond their computational complexity. More specifically, we compare the throughput, error correction capability, flexibility, area efficiency, and energy efficiency of ASIC implementations drawn from 110 papers and use the results for characterizing the advantages and disadvantages of these three codes as well as for avoiding pitfalls and for providing design guidelines.