雙目標優(yōu)化的多用戶MIMO-OFDM系統(tǒng)資源分配方法
發(fā)布時間：2018-08-02 07:35
【摘要】：隨著現(xiàn)代通信對系統(tǒng)吞吐量的需求不斷上升,通過無線資源(時、頻、功率)分配提高系統(tǒng)吞吐量非常重要。在多用戶MIMO-OFDM系統(tǒng)中,由于引入了空分多址,資源在可分配的維度上增加了一倍,使得原本就難以優(yōu)化的資源分配問題更加復(fù)雜�，F(xiàn)有的大多數(shù)研究為了降低分配的復(fù)雜度,對資源分配的自由度做了限制,有些規(guī)定每個子載波上只可以容納一個用戶,這就沒有利用空分多址帶來的頻譜增益;有些集中限定功率在子信道上平均分配,這樣就放棄了利用不同信道的差異帶來的功率增益。另一方面,由于現(xiàn)代社會倡導(dǎo)綠色通信,在一定的系統(tǒng)吞吐量要求下最小化系統(tǒng)總功耗也日漸成為當今4G甚至是未來5G的目標。吞吐量優(yōu)化和功率優(yōu)化在目標訴求上相互矛盾,現(xiàn)有的大多數(shù)文獻都集中在研究優(yōu)化一個目標上,要么是保證系統(tǒng)一定的吞吐量來集中優(yōu)化功率,要么在保證系統(tǒng)一定的總消耗功率的前提下優(yōu)化系統(tǒng)吞吐量,據(jù)我們所知,目前文獻中沒有對多用戶MIMO-OFDM系統(tǒng)中功率和速率進行過聯(lián)合優(yōu)化,不能進行聯(lián)合優(yōu)化的原因有很多,比如存在非線性約束造成優(yōu)化問題非凸難以求解,以及在用傳統(tǒng)的貪婪算法為子載波選擇用戶的時候無法同時兼顧功率和速率的優(yōu)化等,造成解決聯(lián)合優(yōu)化只能采用窮舉法,由于多用戶MIMO-OFDM系統(tǒng)較大的資源自由度,因計算量巨大根本不可行。針對以上問題,本文基于多用戶MIMO-OFDM系統(tǒng),提出了一種功率速率聯(lián)合優(yōu)化算法。即在最小化系統(tǒng)總消耗功率的同時,使得系統(tǒng)吞吐量最大。將用戶對子載波的選擇融入到對功率優(yōu)化和速率優(yōu)化中完成,減少了因為資源自由度過多帶來的問題復(fù)雜性。首先我們建立功率和速率的雙目標優(yōu)化模型,由于存在非線性約束,因此設(shè)計了原問題的對偶問題,解決了原問題的非凸性,將原問題轉(zhuǎn)變?yōu)榱丝梢郧蠼獾耐箖?yōu)化問題,同時證明了原問題和其對偶問題的對偶間隙為0,即證明了通過求解對偶問題的最優(yōu)解也就求得了原問題的最優(yōu)解。在求解對偶問題時,提出了一種解對偶問題的分解和迭代方法,減少了分配的復(fù)雜度。最后,我們通過控制迭代的精度,來最小化系統(tǒng)能耗并最大化系統(tǒng)吞吐量,實現(xiàn)了同時提高功率資源和頻譜資源利用效率的目的。仿真結(jié)果顯示,本文算法在實現(xiàn)的系統(tǒng)吞吐量和消耗的系統(tǒng)總功率方面都優(yōu)于傳統(tǒng)的單目標優(yōu)化算法。
[Abstract]:With the increasing demand for system throughput in modern communication, it is very important to improve the system throughput through the allocation of wireless resources (time, frequency, power). In multiuser MIMO-OFDM systems, the problem of resource allocation, which is difficult to optimize, is complicated by the introduction of spatial division multiple access (SDMA), which results in a doubling of the allocation of resources in the distributable dimension. In order to reduce the complexity of allocation, most of the existing researches restrict the degree of freedom of resource allocation, some stipulate that only one user can be accommodated on each subcarrier, which does not make use of the spectrum gain brought by space-division multiple access (SDMA). In some cases the power is assigned equally over the subchannels, thus giving up the power gain derived from the differences between the different channels. On the other hand, because the modern society advocates green communication, minimizing the total power consumption of the system under certain system throughput requirements is becoming the goal of 4G and even 5G in the future. Throughput optimization and power optimization are contradictory in terms of target demand. Most of the existing literatures focus on optimizing a target, or to ensure a certain throughput of the system to concentrate on power optimization. Either we can optimize the system throughput under the premise of ensuring a certain total power consumption. As far as we know, there is no joint optimization of power and speed in multi-user MIMO-OFDM system, and there are many reasons why the joint optimization can not be carried out. For example, the nonconvex optimization problem is difficult to solve due to the existence of nonlinear constraints, and when the traditional greedy algorithm is used to select users for subcarriers, the power and speed optimization can not be taken into account at the same time, so the solution of joint optimization can only be solved by exhaustive method. Because of the large degree of resource freedom in multiuser MIMO-OFDM system, it is not feasible because of the huge amount of computation. To solve the above problems, this paper proposes a joint power rate optimization algorithm based on multi-user MIMO-OFDM system. While minimizing the total power consumption, the system throughput is maximized. The selection of subcarriers by users is integrated into power optimization and rate optimization, which reduces the complexity of the problem caused by the excessive degree of freedom of resources. First of all, we establish a two-objective optimization model of power and rate. Because of the nonlinear constraints, we design the dual problem of the original problem, solve the non-convexity of the original problem, and turn the original problem into a convex optimization problem that can be solved. At the same time, it is proved that the duality gap of the original problem and its dual problem is 0, that is, the optimal solution of the original problem is obtained by solving the optimal solution of the dual problem. In solving dual problems, a decomposition and iteration method is proposed, which reduces the complexity of allocation. Finally, by controlling the precision of iteration, we minimize the system energy consumption and maximize the system throughput, and achieve the purpose of improving the efficiency of power resources and spectrum resources at the same time. Simulation results show that the proposed algorithm is superior to the traditional single-objective optimization algorithm in terms of system throughput and total power consumption.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN919.3;TN929.53
本文編號：2158663
[Abstract]:With the increasing demand for system throughput in modern communication, it is very important to improve the system throughput through the allocation of wireless resources (time, frequency, power). In multiuser MIMO-OFDM systems, the problem of resource allocation, which is difficult to optimize, is complicated by the introduction of spatial division multiple access (SDMA), which results in a doubling of the allocation of resources in the distributable dimension. In order to reduce the complexity of allocation, most of the existing researches restrict the degree of freedom of resource allocation, some stipulate that only one user can be accommodated on each subcarrier, which does not make use of the spectrum gain brought by space-division multiple access (SDMA). In some cases the power is assigned equally over the subchannels, thus giving up the power gain derived from the differences between the different channels. On the other hand, because the modern society advocates green communication, minimizing the total power consumption of the system under certain system throughput requirements is becoming the goal of 4G and even 5G in the future. Throughput optimization and power optimization are contradictory in terms of target demand. Most of the existing literatures focus on optimizing a target, or to ensure a certain throughput of the system to concentrate on power optimization. Either we can optimize the system throughput under the premise of ensuring a certain total power consumption. As far as we know, there is no joint optimization of power and speed in multi-user MIMO-OFDM system, and there are many reasons why the joint optimization can not be carried out. For example, the nonconvex optimization problem is difficult to solve due to the existence of nonlinear constraints, and when the traditional greedy algorithm is used to select users for subcarriers, the power and speed optimization can not be taken into account at the same time, so the solution of joint optimization can only be solved by exhaustive method. Because of the large degree of resource freedom in multiuser MIMO-OFDM system, it is not feasible because of the huge amount of computation. To solve the above problems, this paper proposes a joint power rate optimization algorithm based on multi-user MIMO-OFDM system. While minimizing the total power consumption, the system throughput is maximized. The selection of subcarriers by users is integrated into power optimization and rate optimization, which reduces the complexity of the problem caused by the excessive degree of freedom of resources. First of all, we establish a two-objective optimization model of power and rate. Because of the nonlinear constraints, we design the dual problem of the original problem, solve the non-convexity of the original problem, and turn the original problem into a convex optimization problem that can be solved. At the same time, it is proved that the duality gap of the original problem and its dual problem is 0, that is, the optimal solution of the original problem is obtained by solving the optimal solution of the dual problem. In solving dual problems, a decomposition and iteration method is proposed, which reduces the complexity of allocation. Finally, by controlling the precision of iteration, we minimize the system energy consumption and maximize the system throughput, and achieve the purpose of improving the efficiency of power resources and spectrum resources at the same time. Simulation results show that the proposed algorithm is superior to the traditional single-objective optimization algorithm in terms of system throughput and total power consumption.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN919.3;TN929.53
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