Researches On Interference Alignment In MIMO Cellular Networks

Nowadays, in the second decade of the new century, people have more communication requirements which are the faster mobile wireless communication speed and higher communication quality.With the development of wireless communication technology, wireless communication environment is becoming more and more complex, interference is the main reason that constrains the communication system performance and user throughput, all kinds of treatments for interference have always been a hot research problem in the field of wireless communications. With the deepening of the research to Interference channel, a new mechanism named Interference Alignment was proposed, interference alignment is a strategy that design precoding vector in the transmitter and simply zero-forcing in the receiver to achive the maximum degrees of freedom.In this thesis, the basic concept of interference alignment was introduced first, research the principle of interference alignment. Two traditional interference alignment algorithms were introduced, the directional alignment algorithm and opportunity interference alignment(OIA1). We analysis the performance of D-IA under perfect and limited feedback scenarios and the performance of OIA1 with different number of users.Next, as the existing interference alignment algorithms do not take the impact on desired signal and receiving the signal to noise ratio (SNR) into account, two iterative interference alignment algorithms are introduced, namely the MP-IA and MSINR-IA algorithm. Studies have shown that the MP-IA algorithm and MSINR-IA algorithm have better average sumrate and bit error rate performance than D-IA algorithm, MP-IA algorithm has the best bit error rate performance, while MSINR-IA algorithm has the best average sumrate performance. In view of the channel estimation error and feedback delay of high mobility in the actual scene, for non ideal channel, we got average sumrate and bit error rate performance of the two algorithms through simulation, which is still better than D-IA algorithm, the advantange of both algorithms will not be affected. With the increase of channel estimation error or delay, the performance of three algorithms will become worse.Finally, this thesis analyze two kinds of opportunistic interference alignment algorithms, namely SLIR-US algorithm and MSE-OIA algorithm. Simulation results show that both SLIR-US algorithm and MSE-OIA algorithm are better than OIA1 algorithm in terms of the system performance of average sumrate and bit error rate; In non ideal channel, as the increase of channel estimation error or delay, the performance of three algorithms will become worse, but the superiority of SLIR-US algorithm and MSE-OIA algorithm will not be affected. In the actual communication scene, if the sumrate requirements are relatively high, SLIR-US algorithm is better; while the bit error rate requirements are high, MSE-OIA algorithm is better.