MIMO信号检测系统量子算法的优化及运用英文小论文 第3页
number is . In the transmitter, the input bit stream converted into parallel data streams through serial/parallel conversion to achieve the output of multiple antennas. Then IFFT transform for each flow. Where IFFT achieve the modulation function of OFDM, it will modulate the slow multiple parallel data streams to sub-carrier which mutual orthogonal simultaneously.
The cyclic prefix (+ CP) in the form of adding guard interval between symbols is applied after IFFT transform, in order to reduce Inter-Symbol Interference (ISI) of system. Finally, send the stream after parallel /serial conversion. In the receiver, first of all, each road of stream should be converted as serial/parallel and remove the cyclic prefix (-CP) after each antenna receives linear superposition signals which send from different antennas and through the MIMO-OFDM channel; Then, doing the FFT transform for follow the receiving antennas respectively from time domain to frequency domain; Finally, the information bit stream recover after the parallel data stream is demodulated by detector and parallel/serial conversion.
The signal detection of MIMO-OFDM system can be completed through signal detection of sub-carriers channel. Since each subcarrier channel can be regarded as a flat fading MIMO channel, therefore, flat fading signal detection algorithm of MIMO system can be directly used into MIMO-OFDM system of sub-channel as corresponding signal detection algorithm of MIMO-OFDM system.
4.2 MIMO-OFDM signal detection scheme based on Quantum Genetic Algorithm
MIMO-OFDM signal detection scheme based on Quantum Genetic Algorithm (QGA) is depicted in Figure 7. The control parameters of QGA in experiment set as section 3.2. To understand the detection performance of QGA, we will compare it with the classical Genetic Algorithm (GA) and Minimum Mean Square Error (MMSE) algorithm. Experimental conditions set as follows: The simulations were performed in a M=N=4 environment and adopt the BPSK modulation. On the channel, adopt AWGN and power control was applied and we assumed perfect knowledge of channel parameters and the channel matrix H at T = 160 symbols per cycle remains the same.
The test result is depicted in Figure 8. Results show that: QGA performance better than GA as the SNR increases.
Fig.7. MIMO-OFDM signal detection scheme based on QGA
Fig.8. Detection performance of QGA when M=N=4
4.3 MIMO-OFDM signal detection scheme based on neural network optimized by QGA
Signal detection scheme of MIMO -OFDM system based on neural network optimized by Quantum Genetic Algorithm is proposed, based research in Section 3.3, shown in Figure 9.
Fig.9. Signal detection scheme of MIMO-OFDM system based on neural network optimized by QGA
To understand the detection performance of proposed scheme, we will compare it with QGA、MMSE and MIMO-OFDM detection scheme based on neural network. The simulations were performed in a M=N=4 environment and adopt the BPSK/QPSK modulation. The control parameters of QGA set as section 3.2 and the clustering RBF set as section 3.3.
The results shown in Figure 10 (left for BPSK, right for QPSK). Results show that: Whether BPSK or QPSK modulation, the detection performance of RBF Network optimized by QGA has improved significantly compared with other intelligent algorithms.
Fig.10.Detection performance of QGA-RBF when M=N=4
5. Conclusion
Optimal detection of signal is a NP (Nondeterministic Polynomial) hard problem under routine conditions. This paper presents a algorithm combined with quantum genetic algorithm and RBF neural network, and for MIMO and MIMO-OFDM signal detection, RBF neural network optimized by QGA has more parallel processing capability and faster convergence than the traditional RBF neural network, for utilization of the Quantum parallel computing and quantum entanglement of quantum computing、better global convergence performance of genetic algorithms and large-scale adaptive parallel processing、rapid learning of RBF neural network. Simulation results show that: The proposed signal detection schemes of MIMO and MIMO-OFDM system have better detection performance than other conventional schemes.
6. References
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Acknowledgements
This work is supported by the Doctoral Foundation of China Ministry of Education (BJ206006) and Research Foundation of NUPT (NY206011).
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