异构蜂窝网络中能效优先的接入机制研究
发布时间：2019-06-27 11:26
【摘要】：新一代以OFDM(Orthogonal Frequency Division Multiplexing)和MIMIO(Multiple-Input Multiple-Output)技术为核心的LTE-Advanced通信系统对通信网络的传输能力提出了更高的要求,因此需要提升单位传输带宽上的数据传输速率,即提高系统的频谱效率。另一方面,通信行业高速发展所带来的高能耗问题也引起了社会的广泛关注。未来移动通信与网络技术的发展必须要面对能量消耗的挑战,要求在优化网络资源的同时降低单位业务量的能量消耗,实现绿色通信。如何降低移动通信网络所消耗的能量,提高移动通信系统的能量效率(Energy Efficiency,EE),用尽可能少的能量传输尽可能多的数据,已成为了当前移动通信研究领域一个新的热点问题。由于传统的宏基站成本高,能耗大,而在蜂窝网络中重叠部署一些低功率节点如中继、微微基站、毫微微基站使得网络异构化,能够增加网络的覆盖范围,提高系统容量。异构网络中由于低功率节点能耗低,较之于部署宏基站能够减少系统的能量消耗;而小基站一般部署在热点区域或者蜂窝网络的盲区,距离用户较近,信号传输的损耗小,能够提高用户的服务质量(QoS)。因此,部署异构网络将宏小区的流量卸载到小基站中是提高系统能量效率的可行方法。然而,新加入的网络元素在传统的蜂窝网络中产生了新的小区,宏小区和低功率节点小区、低功率节点小区之间形成许多小区边缘,使得网络中的干扰分布情形变得复杂。系统中用户的接入小区选择成为最基本的挑战,一方面运营商希望更多的用户接入到低功率节点,最大限度地利用小节点,减少系统的能量消耗,提高系统容量;另一方面,由于低功率节点发射功率低,距离较远的用户受到宏小区的严重干扰。因此,在异构网络中,需要提出一个有效的接入选择方案来提高异构网络系统的能量效率。本文在宏基站和微微基站联合部署的异构网络下,研究用户的选择接入策略对系统的性能影响,提出优化系统性能的接入方案,设计基于动态规划、遗传算法等优化算法的接入机制,为异构网络场景下用户的接入选择提供有效的策略方案。在异构网络中,低功率节点分担宏小区的流量的现象我们称之为流量卸载(Traffic Offloading)。本文首先提出了在宏小区-微微小区联合部署场景下易于实现的流量卸载算法——TO(Traffic Offloading)算法。TO算法是基于用户的测量参数RSRP(Reference Signal Received Power)的接入选择算法,该算法的主要思想是将宏小区用户卸载到满足RSRP和小区负载条件的微微小区中。由于在新型网络中增加了很多的小区边缘,小区边缘的干扰较为严重,本文将部分频谱复用技术(FFR,Fractional Frequency Reuse)与TO算法相结合,提出了TOFFR(Traffic Offloading based on Fractional Frequency Reuse)流量卸载算法。仿真结果表明,两种流量卸载算法都能有效地提高系统的能量效率,而TOFFR算法性能更佳。动态的流量卸载是本文接下来考虑的情形,基于此,本文将动态的流量卸载分为即时流量卸载和延时流量卸载,并且依据用户的卸载模型,对动态流量卸载进行动态规划问题建模,将整体能效优化目标转化成多阶段接入决策的最优化子问题进行求解。在该方案中,考虑了不同的时延参数,利用用户速率限制条件减少算法复杂度。仿真结果显示,与基于RSRP的流量卸载算法相比较,基于动态规划的流量卸载算法能够有效地提高系统的能量效率和流量卸载效率。频谱效率(SE,Spectral Efficiency)也是衡量系统优劣的主要指标之一。本文将系统的能量效率和频谱效率作为优化目标,提出了SE-EE联合优化的接入方案。对于SE-EE的多目标优化问题,首先利用层次分析法分析优化目标SE和EE的判断准则的相对重要性,计算得到SE和EE的相对归一化权重系统,从而将SE和EE的双目标问题转化为一个多项式的单一优化问题。然后利用遗传算法求解得到系统能量效率和频谱效率联合优化。仿真实验证实,与最大化频谱效率和最大化能量效率相比较,本文提出的SE-EE联合优化方案能有效地进行能量效率和频谱效率的折中。
[Abstract]:The new generation of the LTE-Advanced communication system based on the OFDM (Orthogonal Frequency Division Multiplexing) and the MIMIO (Multiple-Input Multiple-Output) technology has higher requirements on the transmission capability of the communication network, and therefore it is necessary to improve the data transmission rate on the unit transmission bandwidth, that is, to improve the spectral efficiency of the system. On the other hand, the high energy consumption caused by the high-speed development of the communication industry has also attracted wide attention from the society. In the future, the development of mobile communication and network technology must face the challenge of energy consumption, and it is required to reduce the energy consumption of unit traffic while optimizing network resources and realize the green communication. How to reduce the energy consumed by the mobile communication network, improve the energy efficiency (EE) of the mobile communication system, and transmit as much data as possible with as little energy as possible has become a new hot issue in the current research field of mobile communication. Because the traditional macro base station cost is high and the energy consumption is large, some low power nodes such as relay, pico base station and femto base station are overlapped and deployed in the cellular network so that the network is isomerized, the coverage of the network can be increased, and the system capacity can be improved. In the heterogeneous network, because the energy consumption of the low power node is low, the energy consumption of the system can be reduced compared with the deployment of the macro base station, and the small base station is generally deployed in the blind area of the hot spot area or the cellular network, the distance is close to the user, the loss of the signal transmission is small, and the service quality (QoS) of the user can be improved. Thus, deploying heterogeneous networks to offload traffic from a macro cell to a small base station is a feasible way to improve system energy efficiency. However, the newly added network elements create new cells in the traditional cellular network, and a number of cell edges are formed between the macro cell and the low power node cell and the low power node cell, so that the interference distribution situation in the network is complicated. the access cell of the user in the system is selected to be the most basic challenge, on the one hand, the operator wants more users to access the low power node, the small node is utilized to the maximum extent, the energy consumption of the system is reduced, the system capacity is improved, and on the other hand, the low power node transmitting power is low, The user farther from the distance is seriously disturbed by the macro cell. Therefore, in the heterogeneous network, a valid access selection scheme is needed to improve the energy efficiency of the heterogeneous network system. In this paper, under the heterogeneous network of the joint deployment of the macro base station and the pico base station, the influence of the user's access strategy on the performance of the system is studied, the access scheme for optimizing the system performance is put forward, and the access mechanism based on the optimization algorithm such as the dynamic programming and the genetic algorithm is designed. And provides an effective strategy scheme for the access selection of a user in a heterogeneous network scene. In a heterogeneous network, the phenomenon of the low power node sharing the traffic of the macro cell is referred to as Traffic Offloading. In this paper, the traffic offload algorithm, which is easy to implement in macro-cell-picocell joint deployment scenario, is proposed. The TO algorithm is an access selection algorithm based on the user's measurement parameter RSRP (Reference Signal Received Power), the main idea of which is to unload the macro cell user into the picocell meeting the RSRP and the cell loading conditions. In this paper, due to the addition of many cell edges in the new network, the interference of the edge of the cell is serious. In this paper, partial frequency spectrum multiplexing (FFR, Fractional Frequency Reuse) is combined with the TO algorithm, and the traffic offload algorithm of the TFFFR (Traffic Offloading based on Frequency Reuse) is put forward. The simulation results show that the two kinds of flow unloading algorithms can effectively improve the energy efficiency of the system, and the TOFD algorithm is better in performance. The dynamic traffic offload is the case to be considered in this paper. Based on this, the dynamic traffic offload is divided into real-time flow unloading and time-delay flow unloading, and the dynamic traffic offload is modeled according to the user's unloading model. And solving the optimization problem of the overall energy efficiency optimization target to the multi-stage access decision. In this scheme, different time delay parameters are considered, and the complexity of the algorithm is reduced by using the user rate limiting condition. The simulation results show that the dynamic programming-based traffic offload algorithm can effectively improve the energy efficiency and discharge efficiency of the system compared with the RSRP-based traffic offload algorithm. The spectral efficiency (SE) is one of the main indexes to measure the quality of the system. In this paper, the energy efficiency and spectral efficiency of the system are used as the optimization targets, and the access scheme of SE-EE joint optimization is put forward. In order to solve the multi-objective optimization problem of SE-EE, first, the relative importance of the decision criterion of the objective SE and EE is analyzed by the analytic hierarchy process, and the relative normalized weight system of SE and EE is calculated, so that the double-objective problem of SE and EE is converted into a single optimization problem of a polynomial. And then using the genetic algorithm to solve the joint optimization of the system energy efficiency and the spectrum efficiency. The simulation experiments confirm that the SE-EE joint optimization scheme proposed in this paper can effectively compromise the energy efficiency and spectral efficiency compared with the maximum spectral efficiency and the maximum energy efficiency.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5
[Abstract]:The new generation of the LTE-Advanced communication system based on the OFDM (Orthogonal Frequency Division Multiplexing) and the MIMIO (Multiple-Input Multiple-Output) technology has higher requirements on the transmission capability of the communication network, and therefore it is necessary to improve the data transmission rate on the unit transmission bandwidth, that is, to improve the spectral efficiency of the system. On the other hand, the high energy consumption caused by the high-speed development of the communication industry has also attracted wide attention from the society. In the future, the development of mobile communication and network technology must face the challenge of energy consumption, and it is required to reduce the energy consumption of unit traffic while optimizing network resources and realize the green communication. How to reduce the energy consumed by the mobile communication network, improve the energy efficiency (EE) of the mobile communication system, and transmit as much data as possible with as little energy as possible has become a new hot issue in the current research field of mobile communication. Because the traditional macro base station cost is high and the energy consumption is large, some low power nodes such as relay, pico base station and femto base station are overlapped and deployed in the cellular network so that the network is isomerized, the coverage of the network can be increased, and the system capacity can be improved. In the heterogeneous network, because the energy consumption of the low power node is low, the energy consumption of the system can be reduced compared with the deployment of the macro base station, and the small base station is generally deployed in the blind area of the hot spot area or the cellular network, the distance is close to the user, the loss of the signal transmission is small, and the service quality (QoS) of the user can be improved. Thus, deploying heterogeneous networks to offload traffic from a macro cell to a small base station is a feasible way to improve system energy efficiency. However, the newly added network elements create new cells in the traditional cellular network, and a number of cell edges are formed between the macro cell and the low power node cell and the low power node cell, so that the interference distribution situation in the network is complicated. the access cell of the user in the system is selected to be the most basic challenge, on the one hand, the operator wants more users to access the low power node, the small node is utilized to the maximum extent, the energy consumption of the system is reduced, the system capacity is improved, and on the other hand, the low power node transmitting power is low, The user farther from the distance is seriously disturbed by the macro cell. Therefore, in the heterogeneous network, a valid access selection scheme is needed to improve the energy efficiency of the heterogeneous network system. In this paper, under the heterogeneous network of the joint deployment of the macro base station and the pico base station, the influence of the user's access strategy on the performance of the system is studied, the access scheme for optimizing the system performance is put forward, and the access mechanism based on the optimization algorithm such as the dynamic programming and the genetic algorithm is designed. And provides an effective strategy scheme for the access selection of a user in a heterogeneous network scene. In a heterogeneous network, the phenomenon of the low power node sharing the traffic of the macro cell is referred to as Traffic Offloading. In this paper, the traffic offload algorithm, which is easy to implement in macro-cell-picocell joint deployment scenario, is proposed. The TO algorithm is an access selection algorithm based on the user's measurement parameter RSRP (Reference Signal Received Power), the main idea of which is to unload the macro cell user into the picocell meeting the RSRP and the cell loading conditions. In this paper, due to the addition of many cell edges in the new network, the interference of the edge of the cell is serious. In this paper, partial frequency spectrum multiplexing (FFR, Fractional Frequency Reuse) is combined with the TO algorithm, and the traffic offload algorithm of the TFFFR (Traffic Offloading based on Frequency Reuse) is put forward. The simulation results show that the two kinds of flow unloading algorithms can effectively improve the energy efficiency of the system, and the TOFD algorithm is better in performance. The dynamic traffic offload is the case to be considered in this paper. Based on this, the dynamic traffic offload is divided into real-time flow unloading and time-delay flow unloading, and the dynamic traffic offload is modeled according to the user's unloading model. And solving the optimization problem of the overall energy efficiency optimization target to the multi-stage access decision. In this scheme, different time delay parameters are considered, and the complexity of the algorithm is reduced by using the user rate limiting condition. The simulation results show that the dynamic programming-based traffic offload algorithm can effectively improve the energy efficiency and discharge efficiency of the system compared with the RSRP-based traffic offload algorithm. The spectral efficiency (SE) is one of the main indexes to measure the quality of the system. In this paper, the energy efficiency and spectral efficiency of the system are used as the optimization targets, and the access scheme of SE-EE joint optimization is put forward. In order to solve the multi-objective optimization problem of SE-EE, first, the relative importance of the decision criterion of the objective SE and EE is analyzed by the analytic hierarchy process, and the relative normalized weight system of SE and EE is calculated, so that the double-objective problem of SE and EE is converted into a single optimization problem of a polynomial. And then using the genetic algorithm to solve the joint optimization of the system energy efficiency and the spectrum efficiency. The simulation experiments confirm that the SE-EE joint optimization scheme proposed in this paper can effectively compromise the energy efficiency and spectral efficiency compared with the maximum spectral efficiency and the maximum energy efficiency.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5
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