Distributed Mimo-ofdm Power Allocation And Adaptive Modulation Techniques,

The next generation of mobile communications requirements of large-capacity and high-quality data transmission, so multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system is drawing intensive attention both from academic and industry. In distributed MIMO-OFDM systems, the antennas at the side of base station are not co-located in the base station, but distributed in different locations. Distributed MIMO is promised as a key technology in future wireless communication systems due to its unique merits such as large system capacity, low transmit power, uniform and enhanced coverage and low radiation on the human body.Compared with centralized MIMO-OFDM system, distributed MIMO-OFDM system has more advantages, and also has its own characteristics. Therefore we need to study the adaptive technology of distributed MIMO-OFDM system to allocate the system cost while improving or guaranteeing system performance.To the above problems of distributed MIMO-OFDM system, the researches on distributed MIMO-OFDM adaptive power distribution, adaptive modulation and signal-to-noise ratio (SNR) estimation which closely related to the adaptive technologies is still limited. Hence, in this paper, we present some research work in the three topics mentioned above:How to improve the performance of distributed MIMO-OFDM system by power allocation of its subcarriers under the constant transmission power is studied in this paper. We propose a power allocation algorithm to the subcarriers of distributed MIMO-OFDM system and its improved algorithm over multipath fading channel. Simulation results show that over large scale fading and COST207 TU channel, the proposed algorithm can obtain about 4 dB performance improvement compared with the distributed MIMO-OFDM space-time block code (STBC) system without power allocation in cases of BPSK modulation, when the BER is 10? 3. The performance of power allocation algorithm in distributed MIMO-OFDM system is better than that of centralized MIMO-OFDM system. Meanwhile, the original algorithm outperforms the algorithm based on subcarrier grouping that makes two subcarriers in one group about 0.4dB.We also focus on reducing the transmission power of distributed MIMO-OFDM system. Based on the water-filling principle and the greedy algorithm, we study an adaptive bit and power allocation algorithm to the subcarriers of distributed MIMO-OFDM system and its improved algorithm over multipath fading channel. The algorithm can minimize the transmission power and meet the required performance at the same time. Simulation results show that over large scale fading and COST207 TU channel, the proposed algorithm can achieve about 2.3 dB performance improvement in the case of MQAM modulation when the BER is 10? 3, compared with the distributed MIMO-OFDM STBC system without adaptive modulation, and the performance gain is even more evident compared with distributed MIMO-OFDM VBLAST system with maximum likelihood detection. The performance of adaptive modulation in distributed MIMO-OFDM system is better than that of centralized MIMO-OFDM system. Meanwhile, the algorithm based on subcarrier grouping that makes two subcarriers in one group has the similar performance with the original algorithm.To the two adaptive systems in this paper, we take into account the impact of adaptive technology to signal power. The additive white gaussian noise (AWGN) channel estimation algorithm can not be used directly in the adaptive systems, so the SNR estimation should be redesigned according to the characteristics of two different adaptive technologies. We give the corresponding noise power estimation methods of two adaptive technologies based on the mean square error. Simulation results show that both the two adaptive technologies have good estimation performance. The estimation algorithm in adaptive power allocation distributed MIMO-OFDM system presents better slightly than that in adaptive modulation distributed MIMO-OFDM system, and its performance is relatively stable. The estimation algorithm in adaptive modulation distributed MIMO-OFDM system has greater estimation error in low and medium SNR.The research results of the distributed MIMO-OFDM adaptive power allocation, distributed MIMO-OFDM adaptive modulation and distributed MIMO-OFDM SNR estimation in this paper can be applied in the signal processing techniques of the next generation distributed MIMO-OFDM based distributed cellular mobile communication networks, distributed wireless local area networks, distributed digital TV/Radio wireless communication networks, which are of great theoretical importance and economic value.