小區(qū)間干擾抑制的協(xié)作波束成形技術(shù)
發(fā)布時間：2018-09-08 17:03
【摘要】：4G無線通信系統(tǒng)和4G Beyond系統(tǒng)下行采用長期演進(jìn)(LTE)技術(shù),以正交頻分多址(OFDMA)為接入方式,同時,為提高頻譜利用率,4G系統(tǒng)采用了同頻覆蓋組網(wǎng)方式。這會對小區(qū)用戶,特別是小區(qū)邊緣用戶造成非常嚴(yán)重的小區(qū)間干擾(ICI)。為了保證小區(qū)內(nèi)所有用戶享受到良好和公平的服務(wù)質(zhì)量,需要一種技術(shù)來對ICI進(jìn)行抑制,提高系統(tǒng)的整體吞吐量,并且保證用戶間的公平性。小區(qū)協(xié)作波束成型技術(shù),是無線標(biāo)準(zhǔn)中多點(diǎn)協(xié)作(CoMP)技術(shù)的一種。它要求基站之間共享信道狀態(tài)信息(CSI)和必要信令,而并不需要共享發(fā)送的數(shù)據(jù),具有較好性能和可實(shí)現(xiàn)性。所以協(xié)作波束成型技術(shù)是這一領(lǐng)域的研究熱點(diǎn)。目前大部分的波束成型技術(shù)都采用中心式的方案,需要基站間高度的同步和信息交互,難以實(shí)施。而且目前現(xiàn)有的技術(shù)很少考慮CSI誤差對系統(tǒng)性能造成的影響,在實(shí)際的場景中會有很嚴(yán)重的性能損失,使用戶陷入中斷。為此,減小波束成型算法開銷、提升算法的魯棒性是國內(nèi)外近期無線通信領(lǐng)域兩個個重要的研究方向。論文圍繞波束成型算法和小區(qū)協(xié)作機(jī)制開展了理論分析研究與計(jì)算機(jī)仿真實(shí)驗(yàn),具體工作如下:(1)針對減小系統(tǒng)開銷和信息交互的需求,本文提出了理想信道模型下的分布式的信干噪比動態(tài)懲罰算法(Distributed Dynamic SINR Pricing Algorithm,DDSPA)。該算法要求每個基站根據(jù)非本小區(qū)用戶的SINR條件以有限的信息交互設(shè)計(jì)SINR懲罰項(xiàng),用來限制本基站對這些用戶的干擾,在保證小區(qū)用戶SINR的情況下優(yōu)化基站的發(fā)送功率。仿真結(jié)果顯示,DDSPA以較快的速度逼近已有的最優(yōu)性能。算法以迭代的方式進(jìn)行,本文分析了迭代收斂的概率和一次迭代需要的信息交互量。(2)針對減小系統(tǒng)開銷和提升魯棒性兩點(diǎn)需求,本文進(jìn)一步提出了基于博弈論的魯棒性算法。為了實(shí)現(xiàn)分布式,這種算法要求基站之間不作任何信息交互,用戶估計(jì)自身受到的小區(qū)間干擾上報(bào)基站,進(jìn)行小區(qū)內(nèi)單獨(dú)優(yōu)化。為了實(shí)現(xiàn)算法的魯棒性,算法考慮了CSI估計(jì)誤差模型和延時誤差模型,以用戶平均最小均方誤差(Average Minimun Square Error,AMSE)為優(yōu)化目標(biāo)。仿真顯示,算法能夠有效地抑制CSI誤差對系統(tǒng)性能的影響。文章也分析了算法收斂概率和收斂速度。(3)為了進(jìn)一步提升系統(tǒng)性能,減小開銷,提高工程可實(shí)現(xiàn)性,本文提出了一種閉式的的魯棒性算法,在發(fā)送功率約束下最小化AMSE和。算法采用采用KKT條件解決優(yōu)化問題,能夠達(dá)到最優(yōu)性能。問題的解為閉式形式,而且無需迭代,系統(tǒng)開銷少。算法也設(shè)計(jì)了基站間的協(xié)作方式,在TDD制式下能夠以分布式的方式實(shí)施,X2接口中僅需要交互信令。仿真結(jié)果顯示,算法能夠進(jìn)一步提高系統(tǒng)性能,并且具有魯棒性。
[Abstract]:4G wireless communication system and 4G Beyond system adopt long-term evolution (LTE) technology, take orthogonal frequency division multiple access (OFDMA) as access mode, at the same time, in order to improve spectrum efficiency and 4G system, the same frequency coverage network is adopted. This can cause very serious cell interference (ICI). For cell users, especially for cell edge users. In order to ensure that all users in the cell enjoy good and fair quality of service, a technology is needed to suppress the ICI, improve the overall throughput of the system, and ensure the fairness between users. Cell cooperative beamforming is a multi-point cooperative (CoMP) technology in wireless standard. It requires the sharing of channel state information (CSI) and necessary signaling between the base stations, without the need to share the transmitted data, so it has better performance and realizability. Therefore, cooperative beamforming technology is a research hotspot in this field. At present, most of the beamforming technologies adopt the central scheme, which requires high synchronization and information exchange between the base stations, so it is difficult to implement. At present, the existing techniques seldom consider the impact of CSI error on system performance, and there will be a serious performance loss in the actual scenario, causing the user to fall into interruption. Therefore, reducing the overhead of beamforming algorithm and improving the robustness of the algorithm are two important research directions in the field of wireless communication at home and abroad. This paper focuses on beamforming algorithm and cell collaboration mechanism, and carries out theoretical analysis and computer simulation experiments. The main work is as follows: (1) to reduce system overhead and information interaction, In this paper, a distributed SINR dynamic penalty algorithm (Distributed Dynamic SINR Pricing Algorithm,DDSPA) based on ideal channel model is proposed. The algorithm requires each base station to design a SINR penalty term with limited information interaction according to the SINR conditions of non-cell users, which is used to limit the interference of the base station to these users and optimize the transmission power of the base station under the condition of guaranteeing the SINR of the cell users. Simulation results show that DDSPA approaches the existing optimal performance at a faster speed. The algorithm is carried out iteratively. In this paper, the probability of iterative convergence and the amount of information interaction required by one iteration are analyzed. (2) for the two requirements of reducing system overhead and improving robustness, a robust algorithm based on game theory is proposed. In order to achieve distribution, the algorithm requires that the base stations do not interact with each other, and the users estimate their own inter-cell interference and report it to the base station for individual optimization in the cell. In order to realize the robustness of the algorithm, the CSI estimation error model and the delay error model are considered, and the user average minimum mean square error (Average Minimun Square Error,AMSE) is taken as the optimization objective. Simulation results show that the algorithm can effectively suppress the effect of CSI error on system performance. This paper also analyzes the convergence probability and convergence speed of the algorithm. (3) in order to further improve the system performance, reduce the overhead and improve the engineering realizability, a closed robust algorithm is proposed to minimize the AMSE sum under transmission power constraints. The KKT condition is used to solve the optimization problem and the optimal performance can be achieved. The solution of the problem is closed form, and without iteration, the system cost is less. The algorithm also designs the mode of cooperation between base stations. Only interactive signaling is needed to implement the X2 interface in a distributed manner under the TDD system. Simulation results show that the algorithm can further improve the system performance and has robustness.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN929.5
[Abstract]:4G wireless communication system and 4G Beyond system adopt long-term evolution (LTE) technology, take orthogonal frequency division multiple access (OFDMA) as access mode, at the same time, in order to improve spectrum efficiency and 4G system, the same frequency coverage network is adopted. This can cause very serious cell interference (ICI). For cell users, especially for cell edge users. In order to ensure that all users in the cell enjoy good and fair quality of service, a technology is needed to suppress the ICI, improve the overall throughput of the system, and ensure the fairness between users. Cell cooperative beamforming is a multi-point cooperative (CoMP) technology in wireless standard. It requires the sharing of channel state information (CSI) and necessary signaling between the base stations, without the need to share the transmitted data, so it has better performance and realizability. Therefore, cooperative beamforming technology is a research hotspot in this field. At present, most of the beamforming technologies adopt the central scheme, which requires high synchronization and information exchange between the base stations, so it is difficult to implement. At present, the existing techniques seldom consider the impact of CSI error on system performance, and there will be a serious performance loss in the actual scenario, causing the user to fall into interruption. Therefore, reducing the overhead of beamforming algorithm and improving the robustness of the algorithm are two important research directions in the field of wireless communication at home and abroad. This paper focuses on beamforming algorithm and cell collaboration mechanism, and carries out theoretical analysis and computer simulation experiments. The main work is as follows: (1) to reduce system overhead and information interaction, In this paper, a distributed SINR dynamic penalty algorithm (Distributed Dynamic SINR Pricing Algorithm,DDSPA) based on ideal channel model is proposed. The algorithm requires each base station to design a SINR penalty term with limited information interaction according to the SINR conditions of non-cell users, which is used to limit the interference of the base station to these users and optimize the transmission power of the base station under the condition of guaranteeing the SINR of the cell users. Simulation results show that DDSPA approaches the existing optimal performance at a faster speed. The algorithm is carried out iteratively. In this paper, the probability of iterative convergence and the amount of information interaction required by one iteration are analyzed. (2) for the two requirements of reducing system overhead and improving robustness, a robust algorithm based on game theory is proposed. In order to achieve distribution, the algorithm requires that the base stations do not interact with each other, and the users estimate their own inter-cell interference and report it to the base station for individual optimization in the cell. In order to realize the robustness of the algorithm, the CSI estimation error model and the delay error model are considered, and the user average minimum mean square error (Average Minimun Square Error,AMSE) is taken as the optimization objective. Simulation results show that the algorithm can effectively suppress the effect of CSI error on system performance. This paper also analyzes the convergence probability and convergence speed of the algorithm. (3) in order to further improve the system performance, reduce the overhead and improve the engineering realizability, a closed robust algorithm is proposed to minimize the AMSE sum under transmission power constraints. The KKT condition is used to solve the optimization problem and the optimal performance can be achieved. The solution of the problem is closed form, and without iteration, the system cost is less. The algorithm also designs the mode of cooperation between base stations. Only interactive signaling is needed to implement the X2 interface in a distributed manner under the TDD system. Simulation results show that the algorithm can further improve the system performance and has robustness.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN929.5
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