互信息量最大化和低復(fù)雜度的全雙工中繼網(wǎng)絡(luò)自干擾消除和干擾對齊算法
doi: 10.11999/JEIT150791
國家自然科學(xué)基金(61271259, 61471076),重慶市教委科學(xué)技術(shù)研究項(xiàng)目(KJ120501, KJ130536),長江學(xué)者和創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃(IRT1299),重慶市科委重點(diǎn)實(shí)驗(yàn)室專項(xiàng)經(jīng)費(fèi)(CSTC)
A Self-interference Cancellation and Interference Alignment Algorithm for Full-duplex Relay Networks with Maximum Mutual Information and Low Complexity
The National Nature Science Foundation of China (61271259, 61471076), Scientific and Technological Research Program of Chongqing Education Commission (KJ120501, KJ130536), Changjiang Scholars and Innovative Research Team (IRT1299), Special funds of Key Laboratory of Chongqing Science and Technology Committee
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摘要: 該文針對多用戶全雙工中繼干擾信道,同時(shí)考慮全雙工中繼自干擾消除及用戶端干擾消除問題。首先,提出了基于最大化全局互信息量的自干擾消除和干擾對齊算法,并具體給出了自干擾消除矩陣的具體求解算法和方案。進(jìn)一步,給出了信號(hào)對齊和干擾抑制的可行性條件,并分析了系統(tǒng)的互信息量和所受干擾噪聲功率,以及系統(tǒng)的自由度。理論分析和仿真結(jié)果顯示,與現(xiàn)有的典型全雙工中繼方案相比,該文算法可以提高系統(tǒng)互信息量和自由度,并有較低誤碼率;另外,該文算法的中繼只需進(jìn)行簡單的功率約束,不需做復(fù)雜的信號(hào)處理,降低了整個(gè)系統(tǒng)的信號(hào)處理復(fù)雜度。Abstract: This paper considers a multi-user full-duplex relay interference channel where self- interference and user interference exist. Firstly, a self-interference cancellation and interference alignment algorithm based on maximum global mutual information is proposed, and then the concrete algorithm and scheme of self-interference cancellation matrix is given. Furthermore, this paper investigates the feasibility conditions of the signal alignment and interference suppression, so as to analyze the mutual information, the interference plus noise power and the degree of freedom of the system. Theoretical analysis and simulation results show that the proposed algorithm can improve the mutual information and the degree of freedom of the system, and reduce the bit error rate compared with the existing typical full-duplex relay scheme. In addition, the relay only needs to do simple power constraints, and it is not necessary to do complex signal processing which reduces the complexity of signal processing for the whole system.
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