Current Issue : October - December Volume : 2017 Issue Number : 4 Articles : 5 Articles
The technique of SNR estimation is one of the key technologies in adaptive\nfrequency hopping system. The methods of channel quality estimation for\nnonlinear continuous phase modulation (CPM) signals have some limitations.\nTherefore, the algorithm of channel quality estimation for CPM signals is\nworthy of further study. Some similar phase characteristics between sampling\nCPM and MPSK motivate us to propose a channel estimation algorithm with\napplications to nonlinear CPM using linear modulation signal processing. A\ncomprehensive analysis of LDPC-CPM schemes using proposed algorithm is\npresented, and simulation results indicate that the proposed method can not\nonly estimate channel quality well but also make the normalized MSE (NMSE)\nof SNR estimate close to/less than 0.1 dB at SNR of 4 dB using short block\ncodes. It shows that the algorithm in this paper is effective enough to estimate\nthe signal to noise ratio (SNR). Meanwhile, the algorithm in this paper reduces\nthe complexity of computation compared with other traditional algorithms....
This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple\nrelays, and one destination. To achieve high spectral efficiency, we assume that a single time slot is dedicated to\nrelaying. Conventional network-coded-based cooperation (NCC) selects the best relay which uses network coding to\nserve the two sources simultaneously. The bit error rate (BER) performance of NCC with channel coding, however, is\nstill unknown. In this paper, we firstly study the BER of NCC via a closed-form expression and analytically show that\nNCC only achieves diversity of order two regardless of the number of available relays and the channel code. Secondly,\nwe propose a novel partial relaying-based cooperation (PARC) scheme to improve the system diversity in the finite\nsignal-to-noise ratio (SNR) regime. In particular, closed-form expressions for the system BER and diversity order of\nPARC are derived as a function of the operating SNR value and the minimum distance of the channel code. We\nanalytically show that the proposed PARC achieves full (instantaneous) diversity order in the finite SNR regime, given\nthat an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR\ngain of PARC over NCC in the SNR region of interest...
This paper deals with the imaging problem for one-stationary bistatic synthetic aperture radar (BiSAR) with highsquint,\nlarge-baseline configuration. In this bistatic configuration, accurate focusing of BiSAR data is a difficult issue\ndue to the relatively large range cell migration (RCM), severe range-azimuth coupling, and inherent azimuthgeometric\nvariance. To circumvent these issues, an enhanced azimuth nonlinear chirp scaling (NLCS) algorithm\nbased on an ellipse model is investigated in this paper. In the range processing, a method combining deramp\noperation and keystone transform (KT) is adopted to remove linear RCM completely and mitigate range-azimuth\ncross-coupling. In the azimuth focusing, an ellipse model is established to analyze and depict the characteristic of\nazimuth-variant Doppler phase. Based on the new model, an enhanced azimuth NLCS algorithm is derived to focus\none-stationary BiSAR data. Simulating results exhibited at the end of this paper validate the effectiveness of the\nproposed algorithm....
In this paper, a novel processing-efficient architecture of a group of inexpensive and computationally incapable small platforms is\nproposed for a parallely distributed adaptive signal processing (PDASP) operation.The proposed architecture runs computationally\nexpensive procedures like complex adaptive recursive least square (RLS) algorithmcooperatively.The proposedPDASP architecture\noperates properly even if perfect time alignment among the participating platforms is not available. An RLS algorithm with the\napplication of MIMO channel estimation is deployed on the proposed architecture. Complexity and processing time of the PDASP\nscheme with MIMO RLS algorithm are compared with sequentially operated MIMO RLS algorithm and liner Kalman filter. It is\nobserved that PDASP scheme exhibits much lesser computational complexity parallely than the sequential MIMO RLS algorithm\nas well as Kalman filter.Moreover, the proposed architecture provides an improvement of 95.83%and 82.29% decreased processing\ntime parallely compared to the sequentially operated Kalman filter and MIMO RLS algorithm for low doppler rate, respectively.\nLikewise, for high doppler rate, the proposed architecture entails an improvement of 94.12%and 77.28...
In order to use the existing automatic identification system (AIS) to provide additional\nnavigation and positioning services, a complete pseudorange measurements solution is presented\nin this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital\nsequences were determined as the timestamps. Monte Carlo simulation was carried out to compare\nthe accuracy of the zero-crossing and differential peak, which are two timestamp detection methods\nin the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic\nmotion characteristics of ships, an optimal estimation method based on the minimum mean square\nerror is proposed to improve detection accuracy. Furthermore, the Ã?± difference filter algorithm was\nused to achieve the fusion of the optimal estimation results of the two detection methods. The results\nshow that the algorithm can greatly improve the accuracy of pseudorange estimation under low\nsignal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes\ncontaining the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China)\nwere performed. The test results show that the pseudorange measurement accuracy was better than\n28 m (ÃÆ?) without any modification of the existing AIS system....
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