DocumentCode :
3158354
Title :
Low complexity partial sampled MMSE channel estimation for downlink OFDMA IEEE 802.16e system
Author :
Galih, Savitri ; Karlina, Riafeni ; Irawan, Ade ; Adiono, Trio ; Kurniawan, Adit ; Iskandar
Author_Institution :
Sch. of Electron. & Inf., Bandung Inst. of Technol., Bandung, Indonesia
fYear :
2009
fDate :
7-9 Jan. 2009
Firstpage :
162
Lastpage :
166
Abstract :
Channel estimation is one of key problems in IEEE 802.16e Orthogonal Frequency Division Multiplexing Access (OFDMA) downlink system. Minimum Mean Square Error (MMSE) channel estimation has been known as a superior performance channel estimation. However, this algorithm has high computational complexity. In this paper, we present low complexity partial-sampled MMSE channel estimation for compromising between complexity and performance. We reduced MMSE channel estimation complexity by partially sampling the MMSE weight matrix. The simulation results show that the bit error rate (BER) performance significantly improved over the least square channel estimation and has comparable BER performance with MMSE channel estimation at low SNR. Depending the sixze of sampling, significant decrease 57 % to 64 % in computational complexity can be achieved.
Keywords :
WiMax; channel estimation; communication complexity; frequency division multiple access; mean square error methods; OFDMA downlink system; bit error rate performance; computational complexity; downlink OFDMA IEEE 802.16e system; least square channel estimation; low complexity partial sampled MMSE channel estimation; minimum mean square error channel estimation; orthogonal frequency division multiplexing access; Bit error rate; Channel estimation; Computational complexity; Downlink; Informatics; Least squares approximation; OFDM; Sampling methods; Signal processing; WiMAX; OFDMA; channel estimation; mobile WiMAX;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Signal Processing and Communication Systems, 2009. ISPACS 2009. International Symposium on
Conference_Location :
Kanazawa
Print_ISBN :
978-1-4244-5015-2
Electronic_ISBN :
978-1-4244-5016-9
Type :
conf
DOI :
10.1109/ISPACS.2009.5383875
Filename :
5383875
Link To Document :
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