Low complexity PAPR reduction method for MIMO-OFDM Systems

• Main Authors: Chun Yu Wang, 王鈞玉
• Other Authors: Ouyang Yuan
• Format: Others
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/97366445111101365677

碩士 === 長庚大學 === 電機工程學系 === 100 === In the wireless communication systems, the goal of everyone that is able to provide higher transmission rates, transmission capacity and transmission quality.Due to multiple-input multiple-output can increase the data throughput, and orthogonal frequency division multiplexing can also be effective against frequency selective fading channel,Therefore,the MIMO and OFDM technology is widely used in 4G wireless systems.However, a major drawback of MIMO-OFDM system is the high peak-to-average power ratio in transmission signal.Cross-Antenna Translation(CAT) and Expanded-CAT as we previously proposed methods to reduce PAPR, but the major drawback of these two methods is that too much number of inverse fast Fourier transforms (IFFT’s)and thus require high computational complexity.Therefore, in this article, we propose a method to reduce CAT and Expanded CAT computational complexity of the new structure.In the new structure, the combination we had to do is conversion from the frequency domain to the time domain.At first, we will define two basic elements.These two basic elements will first pass through IFFT to the time domain,than we used six different conversions to produce the same time-domain signal with original CAT and Expanded-CAT method in the time domain. This can effectively reduce the number of IFFT.From the simulation results,we can see there has the same PAPR reduction performance with the new structure and the original CAT and Expanded CAT methods.In the comparison of computational complexity,for example, we use the Expanded CAT method.In the new structure of the number of complex multiplications will be reduced from 64^M[(LN)log(N)/log(2)+LN] to M/2*Q[(LN)log(N)/log(2)-(LN)log(LM)/log(2)+LN] .On the number of complex additions will be reduced from 2*64^M[(LN)log(N)/log(2)] to M*Q[(LN)log(LN)/log(2)-(LN)log(LM)/log(2)]+2*64^M*LN+3*M*Q*LN where M is the number of Subblock, Q is the number of antennas, N is the number of subcarriers, L stands for oversampling factor.