Abstract
With the rapid growth of network users, how to increase the system capacity has become an urgent problem for the current communication system in the case of limited spectrum resources. The introduction of multi-user systems has increased system capacity, but it has also led to inter-user interference, which has further affected system capacity. To solve the multi-user interference problem, interference alignment is introduced. Interference Alignment (IA) is an interference cancellation technique that effectively eliminates the effects of interfering signals by compressing the interfering signal into a space independent of the desired signal and then forcing the interfering signal to zero at the receiving end. However, in practical applications, interference-aligned transceivers require a joint design, which is often difficult to achieve. The traditional approach is to mathematically expect it, but it also leads to some degree of irrationality in the transceiver design. In this paper, based on the traditional least square interference alignment (LS-IA) algorithm, a symbol-detection-assisted least square interference alignment (SDA-LS-IA) algorithm is proposed for its shortcomings in transceiver algorithm design. Firstly, based on the precoding matrix and the zero-forcing matrix of the transceiver designed by the traditional LS-IA, the symbol detection is performed, and then the transceiver is designed again according to the detection symbol, and then the symbol detection is performed. The computer simulation proves that the proposed algorithm has better anti-interference performance than the traditional LS-IA.
Highlights
With the development of the global mobile market, the popularity of smart terminals and the development of the Internet of Things business, mobile data traffic has grown rapidly [1,2,3]
Based on the traditional LS-Interference Alignment (IA), this paper proposes a symbol-detection-assisted least square interference alignment (SDA-LS-IA) algorithm, which is a LS-based transceiver design
14) is small or even no gain; when β is too large, due to the iterations number of equation (11-12) is small, and the matrices Ui and Vi do not converge, resulting in the signal detected by equation (2) being substantially mismatched with the actual transmitted signal, that is to say,the mean square error (MSE) and the bit error rate (BER) are large
Summary
With the development of the global mobile market, the popularity of smart terminals and the development of the Internet of Things business, mobile data traffic has grown rapidly [1,2,3]. The main idea of IA is to precode the signal before it is sent, and perform zero-forcing filtering after receiving the signal to separate the signal into two separate spaces, eliminating interference. It shows that the theoretical maximum degree of freedom of the K user interference channel can reach K / 2. An one-time linear precoding method is proposed on a single time slot frequency to achieve optimal degrees of freedom [6] It requires a joint design of the transmitter and receiver, which is often difficult to implement in practice. The proposed SDA-LS-IA algorithm has better performance than the traditional LS-IA by computer simulation
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