A Joint QR-LS Based Coarse-Fine Channel Estimation and QR-LRL Detection for Mobile WiMAX 802.16m
01 Dec 2011-pp 1-5
TL;DR: This work extended the previous work of QR-RLS based MIMO(Multiple input Multiple output) channel estimation to Mobile Wimax 802.16m system, where both preamble and pilots are jointly used for robust channel estimation.
Abstract: In this paper, We extended our previous work of QR-RLS based MIMO(Multiple input Multiple output) channel estimation to Mobile Wimax 802.16m system. Mobile wimax system provides high data rate, also fulfills user's requirement like VOD(Video on demand)at very high vehicle speed and also provides better cell coverage area. Channel estimation is crucial part to achieve this goals especially in fast fading environment. Generally, Mobile Wimax systems uses Preamble and Pilots for channel estimation purpose. In the proposed method both preamble and pilots are jointly used for robust channel estimation. At First, QR-RLS Estimator uses Preamble for coarse channel estimation at start of every frame. Once the coarse channel is estimated, then pilots (scattered throughout time-frequency grid) are jointly used with the coarse channel component to derive the channel fading rate. This fading rate is then used to finely estimate the channel at pilot as well as data subcarrier. Thus robust estimation results without adding any overhead. Jointly estimated channel is then used with QR-LRL based data detection, where hard decision values are calculated. Simulation results are shown under various slow-fast channel fading conditions. Results are compared with pilot based channel estimation with LS(least square) interpolation, which shows that joint coarse-Fine estimation gives better performance.
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01 Sep 2020
TL;DR: It is observed that MMSE-IRC receiver successfully mitigates the interferences compared to only MMSE based receiver and simulation results also show performance improvement over various parameters like sum-rate, interference mitigation and BER compared to prior technologies i.e. 4G-LTE, WiMAX, etc.
Abstract: In this work, we investigated the performance of single input single output (SISO) downlink channel considering 5G new radio (NR). A number of parameters such as different modulation schemes, channel coding with varying code rates, scalable numerology μ and 3GPP channel models have been considered for evaluation. In addition, the minimum mean square error-interference rejection combining (MMSE-IRC) technique for interference mitigation and bit error rate (BER) performance is analyzed and presented. We also compared the sum-rate performance of LTE and 5G NR. It is observed that MMSE-IRC receiver successfully mitigates the interferences compared to only MMSE based receiver. Simulation results also show performance improvement over various parameters like sum-rate, interference mitigation and BER compared to prior technologies i.e. 4G-LTE, WiMAX, etc.
3 citations
Cites background from "A Joint QR-LS Based Coarse-Fine Cha..."
...e 4G (LTE, WiMAX) in terms of BER, sum-rate and interference mitigation [8] ....
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01 Mar 2016
TL;DR: This paper introduces a novel joint channel estimation and detection method for very large MIMO system that uses enlarged QR-LRL based ordered Detection jointly with the EVD based estimated channel, which not only results in less complexity but also provides better BER performance compared to conventional EVD-ILSP method.
Abstract: This paper introduces a novel joint channel estimation and detection method for very large MIMO system. Conventionally, orthogonal pilot sequences are used to determine correct CSI(channel state information). It falls behind due to pilot contamination and spectral inefficiency in large MIMO systems. Many authors suggested promising approaches of blind and semi blind channel estimation[2][3], which work well with a trade-off for complexity. Author[1] suggested EVD-ILSP based estimation, which results in high spectral efficiency compared to conventional method, However, suffers from high complexity due to ILSP method. Here, the proposed method uses enlarged QR-LRL[5] based ordered Detection jointly with the EVD based estimated channel, which not only results in less complexity but also provides better BER performance compared to conventional EVD-ILSP method. Thus the throughput of large MIMO system is increased with reduced complexity. Simulation results demonstrate remarkable improvement in the performance of proposed method over conventional method.
References
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27 Jun 2010
TL;DR: In this article, a novel method for OFDM-MIMO channel estimation using QR-RLS(square root-recursive least square) estimator is presented, which uses QR-factorization of the correlation matrix and thus avoids square matrix inverse results in less computations as well as less roundoff error.
Abstract: In this paper, A novel method for OFDM-MIMO channel estimation using QR-RLS(Square Root-Recursive Least Square) estimator is presented. Preamble aided channel estimation is performed in time-domain, estimated channel is then used for data detection during data transmission within that frame. The performance results are compared with wiener RLS channel estimator in terms of channel estimator MSE performance. Wiener based Standard-RLS estimator uses correlation matrix inverse for estimation and recursion, Correlation matrix may become singular under low noise/high correlated channels, results in round-off error. On the other hand, Square-Root estimator use QR-factorization of the correlation matrix and thus avoids square matrix inverse results in less computations as well as less round-off error. The simulation results shows that square root QR-RLS estimator give better results in terms of Estimation error.
3 citations