非完善CSIT下MIMO系統(tǒng)能效優(yōu)化方法研究
發(fā)布時間：2018-09-19 12:53
【摘要】：能量效率(Energy Efficiency,EE)已經成為第五代移動通信系統(tǒng)(5G)的關鍵性能指標(Key Performance Indicator,KPI)之一。提高無線通信系統(tǒng)的能量效率能夠有效降低移動網絡運營商(Mobile Network Operator,MNO)的基礎建設費用(Capital Expenditure, CAPEX)和運營費用(Operation Expenditure, OPEX),同時也能夠大幅度降低信息通信技術(Information Communication Technology,ICT)的溫室氣體排放量,實現(xiàn)低碳社會的目標。另一方面,多輸入多輸出(Multiple Input Multiple Output,MIMO)技術已經成為包括5G在內的很多無線通信標準的關鍵技術,極大的提高了頻譜效率(Spectral Efficiency, SE)。考慮到實際的MIMO系統(tǒng)的發(fā)送端信道狀態(tài)信息(Channel State Information at Transmitter,CSIT)往往并不完善,因此很有必要針對非完善CSIT下的MIMO系統(tǒng)進行能量效率優(yōu)化方法的研究。 本文關注非完善CSIT下的下行MIMO系統(tǒng)能量效率優(yōu)化方法的研究。由于預編碼技術是MIMO系統(tǒng)獲得分集和復用增益的基礎,因此本文首先在受限的CSIT不確定度模型下針對多用戶MIMO(Multiuser MIMO,MU-MIMO)系統(tǒng)研究了能量效率優(yōu)化的預編碼設計問題。另外,考慮到訓練序列開銷與能量效率之間存在折中關系,為此本文分別針對基于訓練的多用戶MIMO系統(tǒng)和多小區(qū)MIMO系統(tǒng)研究了能量效率優(yōu)化方法。 首先,預編碼技術是提高多用戶MIMO系統(tǒng)性能的重要手段。因此,本文在受限的CSIT不確定度模型下研究了能量效率優(yōu)化的預編碼設計問題。該問題是一個非凸的分數(shù)規(guī)劃。為了求解該問題,本文首先運用用戶可達速率與最小均方誤差(Minimum Mean Square Error,MMSE)的對應關系以及min-max不等式把原問題轉化為它的具有分數(shù)和max-min形式的下界問題。接著利用分數(shù)規(guī)劃定理把分數(shù)形式的問題轉化為帶參數(shù)的、減數(shù)形式的優(yōu)化問題,并利用拉格朗日對偶性將該max-min問題轉化為max-max的形式,進一步提出了能夠保證收斂性的迭代求解算法。仿真結果表明,本文所提出的算法相比于已有的算法能夠顯著提高多用戶MIMO系統(tǒng)的能量效率。 其次,基站獲得CSIT需要付出一定的訓練序列開銷,訓練序列功率過小會導致CSIT準確度很低,造成能量效率的下降；訓練序列功率過大則會導致速率增益不能補償訓練序列的能耗,同樣也會降低能量效率,因此,在訓練序列功率和能量效率之間存在折中關系,需要仔細研究。本文針對基于訓練的多用戶MIMO系統(tǒng)研究了能量效率優(yōu)化方法,形成了能效優(yōu)化的功率分配問題。針對CSIT不可見的事實提出一種兩步優(yōu)化方法,分別優(yōu)化各態(tài)歷經能量效率和瞬時能量效率。在各態(tài)歷經能量效率的優(yōu)化中,本文首先推導獲得了各態(tài)歷經可達速率的更緊致下界,然后把原問題轉化為關于各態(tài)歷經能量效率下界的優(yōu)化問題,并證明了它關于訓練功率和數(shù)據功率是聯(lián)合擬凹的,進一步提出了一種交替優(yōu)化求解算法。在瞬時能量效率的優(yōu)化中,發(fā)送端采用基于各態(tài)歷經能量效率優(yōu)化得到的訓練序列功率發(fā)送訓練序列,接收端進行信道估計得到有誤差的信道狀態(tài)信息,并據此預測瞬時能量效率,進一步提出了一種用于優(yōu)化數(shù)據信號發(fā)送功率的瞬時能量效率優(yōu)化算法。仿真結果表明,本文所提出的兩步能量效率優(yōu)化算法相比于只優(yōu)化各態(tài)歷經能量效率的算法和頻效優(yōu)化的算法均能提高多用戶MIMO系統(tǒng)的能量效率。 另外,單小區(qū)傳輸(Single Cell Processing, SCP)和多小區(qū)協(xié)作波束成型(Coordinated Beamforming, CBF)是多小區(qū)MIMO系統(tǒng)中兩種典型的傳輸模式,考慮到用戶可能處于不同的位置,采用不同傳輸模式會帶來不同的能量效率。因此,本文形成了基于訓練的多小區(qū)MIMO系統(tǒng)中考慮最小速率限制的能量效率優(yōu)化問題。該優(yōu)化問題可以表示成關于數(shù)據信號功率、訓練信號功率、傳輸模式的多變量混合分數(shù)規(guī)劃。本文提出了各態(tài)歷經能量效率的近似表達式,然后基于該近似表達式提出了優(yōu)化發(fā)送功率的兩步算法。第一步,忽略最小速率限制,提出一種交替優(yōu)化算法來求解無約束的能量效率優(yōu)化問題；第二步,判斷第一步的解是否滿足最小速率限制條件,如果滿足則算法結束,否則將考慮最小速率約束的問題轉化為最小化功耗的問題并提出一種線性規(guī)劃算法進行求解。這兩個算法都能夠保證收斂性。在優(yōu)化發(fā)送功率之后,本文提出采用遍歷搜索的方法得到能效優(yōu)化的傳輸模式。仿真結果表明,所提出的能量效率優(yōu)化算法相比于一直以最大功率進行發(fā)送的頻效優(yōu)化的基準算法在最小速率限制較低時能夠獲得能量效率的較大增益。而最小速率限制條件也會影響到最優(yōu)傳輸模式的選擇,限制條件越苛刻,系統(tǒng)越傾向于采用協(xié)作波束成型傳輸模式。原因在于：基站需要提高發(fā)送功率以滿足較高的最小速率限制條件,增大了小區(qū)間干擾(Inter-Cell Interference, ICI),使得系統(tǒng)能量效率受限于小區(qū)間干擾,因此,基站就越傾向于采用協(xié)作波束成型傳輸模式消除小區(qū)間干擾,提高多小區(qū)系統(tǒng)的能量效率 本文首先在受限的CSIT誤差模型下針對多用戶MIMO系統(tǒng)提出了能效優(yōu)化的預編碼設計方法,然后分別在基于訓練的多用戶MIMO系統(tǒng)和多小區(qū)MIMO系統(tǒng)中提出了能效優(yōu)化方法。本文研究結果對于如何提高非完善CSIT下的MIMO系統(tǒng)能量效率具有重要的參考價值。
[Abstract]:Energy Efficiency (EE) has become one of the key performance indicators (KPIs) of the fifth generation mobile communication systems (5G). Improving the energy efficiency of wireless communication systems can effectively reduce the capital Expenditure (CAPEX) and transportation costs of mobile network operators (MNO). Operational Expenditure (OPEX) can also significantly reduce greenhouse gas emissions from information communication technology (ICT) and achieve the goal of a low carbon society. On the other hand, MIMO technology has become a lot of wireless including 5G. The key technology of communication standard greatly improves the spectral efficiency (SE). Considering that the actual transmitter channel state information (CSIT) of MIMO system is not perfect, it is necessary to study the optimization method of energy efficiency for MIMO system under imperfect CSIT. Study.
This paper focuses on the study of energy efficiency optimization methods for downlink MIMO systems under imperfect CSIT. Since precoding technology is the basis for obtaining diversity and multiplexing gains for MIMO systems, the precoding presupposition of energy efficiency optimization for multiuser MIMO (MU-MIMO) systems under constrained CSIT uncertainty model is studied in this paper. In addition, considering the tradeoff between training sequence overhead and energy efficiency, this paper studies the energy efficiency optimization methods for training-based multi-user MIMO systems and multi-cell MIMO systems.
First of all, precoding technology is an important means to improve the performance of multi-user MIMO systems. Therefore, this paper studies the precoding design problem of energy efficiency optimization under the constrained CSIT uncertainty model. This problem is a non-convex fractional programming. To solve this problem, user reachable rate and minimum mean square error (Minim) are first used. The corresponding relation of UM Mean Square Error (MMSE) and min-max inequality transform the original problem into its lower bound problem with fractional and max-min forms. Then the fractional form problem is transformed into a parametric, minus form optimization problem by using the fractional programming theorem, and the max-min problem is transformed into a max-min problem by using Lagrange duality. In the form of - max, an iterative algorithm is proposed to guarantee the convergence. Simulation results show that the proposed algorithm can significantly improve the energy efficiency of multi-user MIMO systems compared with the existing algorithms.
Secondly, the base station needs to pay a certain amount of training sequence overhead to obtain CSIT, the training sequence power is too small will lead to low accuracy of CSIT, resulting in a decrease in energy efficiency; training sequence power is too large will lead to the rate gain can not compensate for training sequence energy consumption, also will reduce energy efficiency, therefore, in the training sequence power and energy efficiency. There is a trade-off between rates, which needs careful study. In this paper, the energy efficiency optimization method is studied for training-based multi-user MIMO system, and the power allocation problem of energy efficiency optimization is formed. In the optimization of energy efficiency, a more compact lower bound of the ergodic reachable rate of each state is derived firstly, and then the original problem is transformed into an optimization problem about the lower bound of ergodic energy efficiency of each state. It is proved that the training power and data power are joint quasi-concave, and an alternating optimization algorithm is proposed. In the optimization of instantaneous energy efficiency, the transmitter uses the training sequence power transmission training sequence based on ergodic energy efficiency optimization, and the receiver gets the channel state information with errors by channel estimation, and predicts the instantaneous energy efficiency accordingly. A new instantaneous energy used to optimize the transmission power of the data signal is proposed. Simulation results show that the two-step energy efficiency optimization algorithm proposed in this paper can improve the energy efficiency of multi-user MIMO systems compared with the algorithms that only optimize ergodic energy efficiency and frequency efficiency optimization.
In addition, SCP (Single Cell Processing) and CBF (Coordinated Beam Forming) are two typical transmission modes in multi-cell MIMO systems. Considering that users may be in different locations, different transmission modes will bring different energy efficiency. This optimization problem can be expressed as a multivariate mixed fractional programming with respect to data signal power, training signal power and transmission mode. An approximate expression of ergodic energy efficiency is presented in this paper. Based on this approximate expression, the optimal transmission is proposed. In the first step, an alternative optimization algorithm is proposed to solve the unconstrained energy efficiency optimization problem, ignoring the minimum rate constraint. In the second step, it is determined whether the solution of the first step satisfies the minimum rate constraint condition, and if it satisfies the minimum rate constraint, the algorithm is terminated. A linear programming algorithm is proposed to solve the problem of energy consumption. Both algorithms can guarantee the convergence. After optimizing the transmission power, an ergodic search method is proposed to optimize the transmission mode of energy efficiency. The benchmark algorithm for frequency-efficiency optimization can achieve greater energy efficiency gains when the minimum rate constraint is low. The minimum rate constraint also affects the selection of the optimal transmission mode. The more severe the constraint conditions are, the more likely the system is to adopt cooperative beamforming transmission mode. Higher minimum rate constraint enhances inter-cell interference (ICI), which limits the energy efficiency of the system to inter-cell interference. Therefore, the base station is more inclined to adopt cooperative beamforming transmission mode to eliminate inter-cell interference and improve the energy efficiency of multi-cell system.
In this paper, a precoding design method of energy efficiency optimization for multi-user MIMO systems based on constrained CSIT error model is proposed firstly, and then energy efficiency optimization methods are proposed for training-based multi-user MIMO systems and multi-cell MIMO systems respectively. Important reference value.
【學位授予單位】：中國科學技術大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN919.3
本文編號：2250179
[Abstract]:Energy Efficiency (EE) has become one of the key performance indicators (KPIs) of the fifth generation mobile communication systems (5G). Improving the energy efficiency of wireless communication systems can effectively reduce the capital Expenditure (CAPEX) and transportation costs of mobile network operators (MNO). Operational Expenditure (OPEX) can also significantly reduce greenhouse gas emissions from information communication technology (ICT) and achieve the goal of a low carbon society. On the other hand, MIMO technology has become a lot of wireless including 5G. The key technology of communication standard greatly improves the spectral efficiency (SE). Considering that the actual transmitter channel state information (CSIT) of MIMO system is not perfect, it is necessary to study the optimization method of energy efficiency for MIMO system under imperfect CSIT. Study.
This paper focuses on the study of energy efficiency optimization methods for downlink MIMO systems under imperfect CSIT. Since precoding technology is the basis for obtaining diversity and multiplexing gains for MIMO systems, the precoding presupposition of energy efficiency optimization for multiuser MIMO (MU-MIMO) systems under constrained CSIT uncertainty model is studied in this paper. In addition, considering the tradeoff between training sequence overhead and energy efficiency, this paper studies the energy efficiency optimization methods for training-based multi-user MIMO systems and multi-cell MIMO systems.
First of all, precoding technology is an important means to improve the performance of multi-user MIMO systems. Therefore, this paper studies the precoding design problem of energy efficiency optimization under the constrained CSIT uncertainty model. This problem is a non-convex fractional programming. To solve this problem, user reachable rate and minimum mean square error (Minim) are first used. The corresponding relation of UM Mean Square Error (MMSE) and min-max inequality transform the original problem into its lower bound problem with fractional and max-min forms. Then the fractional form problem is transformed into a parametric, minus form optimization problem by using the fractional programming theorem, and the max-min problem is transformed into a max-min problem by using Lagrange duality. In the form of - max, an iterative algorithm is proposed to guarantee the convergence. Simulation results show that the proposed algorithm can significantly improve the energy efficiency of multi-user MIMO systems compared with the existing algorithms.
Secondly, the base station needs to pay a certain amount of training sequence overhead to obtain CSIT, the training sequence power is too small will lead to low accuracy of CSIT, resulting in a decrease in energy efficiency; training sequence power is too large will lead to the rate gain can not compensate for training sequence energy consumption, also will reduce energy efficiency, therefore, in the training sequence power and energy efficiency. There is a trade-off between rates, which needs careful study. In this paper, the energy efficiency optimization method is studied for training-based multi-user MIMO system, and the power allocation problem of energy efficiency optimization is formed. In the optimization of energy efficiency, a more compact lower bound of the ergodic reachable rate of each state is derived firstly, and then the original problem is transformed into an optimization problem about the lower bound of ergodic energy efficiency of each state. It is proved that the training power and data power are joint quasi-concave, and an alternating optimization algorithm is proposed. In the optimization of instantaneous energy efficiency, the transmitter uses the training sequence power transmission training sequence based on ergodic energy efficiency optimization, and the receiver gets the channel state information with errors by channel estimation, and predicts the instantaneous energy efficiency accordingly. A new instantaneous energy used to optimize the transmission power of the data signal is proposed. Simulation results show that the two-step energy efficiency optimization algorithm proposed in this paper can improve the energy efficiency of multi-user MIMO systems compared with the algorithms that only optimize ergodic energy efficiency and frequency efficiency optimization.
In addition, SCP (Single Cell Processing) and CBF (Coordinated Beam Forming) are two typical transmission modes in multi-cell MIMO systems. Considering that users may be in different locations, different transmission modes will bring different energy efficiency. This optimization problem can be expressed as a multivariate mixed fractional programming with respect to data signal power, training signal power and transmission mode. An approximate expression of ergodic energy efficiency is presented in this paper. Based on this approximate expression, the optimal transmission is proposed. In the first step, an alternative optimization algorithm is proposed to solve the unconstrained energy efficiency optimization problem, ignoring the minimum rate constraint. In the second step, it is determined whether the solution of the first step satisfies the minimum rate constraint condition, and if it satisfies the minimum rate constraint, the algorithm is terminated. A linear programming algorithm is proposed to solve the problem of energy consumption. Both algorithms can guarantee the convergence. After optimizing the transmission power, an ergodic search method is proposed to optimize the transmission mode of energy efficiency. The benchmark algorithm for frequency-efficiency optimization can achieve greater energy efficiency gains when the minimum rate constraint is low. The minimum rate constraint also affects the selection of the optimal transmission mode. The more severe the constraint conditions are, the more likely the system is to adopt cooperative beamforming transmission mode. Higher minimum rate constraint enhances inter-cell interference (ICI), which limits the energy efficiency of the system to inter-cell interference. Therefore, the base station is more inclined to adopt cooperative beamforming transmission mode to eliminate inter-cell interference and improve the energy efficiency of multi-cell system.
In this paper, a precoding design method of energy efficiency optimization for multi-user MIMO systems based on constrained CSIT error model is proposed firstly, and then energy efficiency optimization methods are proposed for training-based multi-user MIMO systems and multi-cell MIMO systems respectively. Important reference value.
【學位授予單位】：中國科學技術大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN919.3
【參考文獻】
相關期刊論文 前3條
1 劉爽;朱凱;董宸;;基于PLC一維極軸自動控制的對日跟蹤系統(tǒng)[J];工業(yè)控制計算機;2010年01期
2 ;Multi-user MIMO downlink eigen-mode transmission over jointly correlated MIMO channels[J];Science China(Information Sciences);2011年10期
3 XU Jie;LI ShiChao;QIU Ling;SLIMANE Ben S.;YU ChengWen;;Energy efficient downlink MIMO transmission with linear precoding[J];Science China(Information Sciences);2013年02期
，本文編號：2250179
本文鏈接：http://sikaile.net/kejilunwen/wltx/2250179.html
最近更新
教材專著
