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RISS 인기검색어
- 검색키워드
- 저자 : Robert C. Qiu (검색결과 3 건)
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NOLD: A Neural-Network Optimized Low-Resolution Decoder for LDPC Codes
Lei Chu,Huanyu He,Ling Pei,Robert C. Qiu 한국통신학회 2021 Journal of communications and networks Vol.23 No.3
The min-sum (MS) algorithm can decode Low-densityparity-check (LDPC) codes with low computational complexity atthe cost of slight performance loss. It is an effective way to realizehardware implementation of the min-sum decoder by quantizingthe floating belief messages (i.e., check-to-variable messages andvariable-to-check messages) into low-resolution (i.e., 2–4 bits) ver sions. However, such a way can lead to severe performance degra dation due to the finite precision effect. In this paper, we proposea neural-network optimized low-resolution decoding (NOLD) al gorithm for LDPC codes to deal with the problem. Specifically,the optimization of decoding parameters (i.e., scaling factors andquantization step) is achieved in a hybrid way, in which we con catenate a NOLD decoder with a customized neural network. Alllearnable parameters associated with the decoding parameters areassigned to each neuron in the proposed method. What’s more, wedesign a new activation function whose outputs are close to the em ployed quantizer ones when network parameters are finally opti mized off-line. Finally, the performance of the proposed method isverified by numerous experiments. For the case of 2-bit decoding,the proposed approach significantly outperforms several conven tional decoders at the expense of slightly increased off-line trainingtime. Besides, the proposed method with 4-bit quantization incursonly 0.1 dB performance loss compared with the floating min-sumdecoder at the coded bit-error-rate of 10−5. Moreover, we showthat the proposed NOLD decoder works over a wide range of chan nel conditions for regular and irregular LDPC codes. Simulationcode for reproductive results is publicly available1.
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Behavior Propagation in Cognitive Radio Networks: A Social Network Approach
Husheng Li,Ju Bin Song,Chien-fei Chen,Lifeng Lai,Qiu, Robert C. IEEE 2014 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Vol.13 No.2
<P>A key feature of cognitive radio network is the intelligence of secondary users who can collaborate to improve the system performance. The collaboration in terms of channel recommendation is studied in this paper. The recommendation mechanism results in dynamics of the channel preferences of secondary users, thus causing a behavior propagation in a social network. For cognitive radio networks having a grid topology, the ergodicity of the dynamics is studied using the model of interacting particles in nonequilibrium statistical mechanics. For networks having a grid topology or being randomly deployed, mean field descriptions using ordinary differential equation are used to explicitly describe the dynamics of behavior propagation. The analytic results are demonstrated by numerical simulations.</P>
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