上行干扰定位与优化浅析

GSM移动通信技术在我国迅速发展,目前已经发展相当成熟的阶段,在实际的网络优化工作中,发现GSM系统受到的上行干扰问题已经成为网络优化中一个不容忽视的重要问题。干扰会使系统掉话率增加,减少基站的覆盖范围,降低通话质量,使网络指标和用户的通话质量受到严重影响。本文通过分析各种干扰类型、干扰特性,阐述如何进行干扰定位优化,达到消除干扰影响、改善网络质量的目的,最后简单介绍目前抗干扰技术。     

GSM网络优化——干扰分析

网络优化是GSM系统建设中一个非常重要的过程,其目的是提高网络通信质量.文章先介绍了GSM网络干扰的分类,然后分析了产生网络干扰的原因,以及干扰的定位方法,最后结合移动通信网络优化工程实例,介绍如何分析测试数据,掌握网络实际运行情况,通过调整频率规划、小区参数达到抑制干扰的目的,从而提高系统性能,改善网络服务质量,使现有网络资源获得最佳效益.     

GSM网络优化-干扰分析

网络优化是GSM系统建设中一个非常重要的过程,其目的是提高网络通信质量.本文先介绍了GSM网络干扰的分类,然后分析了产生网络干扰的原因,以及干扰的定位方法,最后结合移动通信网络优化工程实例,介绍如何分析测试数据,掌握网络实际运行情况,通过调整频率规划、小区参数达到抑制干扰的目的,从而提高系统性能,改善网络服务质量,使现有网络资源获得最佳效益.     

5G无线网络下的智能干扰管理技术研究

在5G技术中,超密集组网技术是非常关键的,这项技术能够满足在未来人们对于数据流量的需求.可是密集的网络部署对于网络会有较强的干扰,为实现对5G技术中的超密集网络的全面有效的控制,对于干扰技术的管理和应用我们要更加注重.本文中,主要针对如何有效处理干扰因子的相关技术基础上进行分析,对5G无线网络技术中智能处理干扰管理技术的应用进行探究,可以作为以后5G网络技术发展的过程中干扰技术的应用参考.     

浅谈CDMA网干扰定位和排查

在CDMA系统中,如何最大限度减少干扰对网络的影响,是广大网络优化人员共同关注的课题。该文重点介绍CDMA网内部和外部的干扰,结合日常网优工作中的干扰定位排查情况,提供干扰排查方法和部分案例。     

一种TD-LTE混合干扰分析及解决系统

TD-LTE网络采用同频段组网,尽管提高频谱利用效率但相邻小区间干扰比较严重,因而良好的覆盖和干扰控制对网络性能意义重大。传统的干扰排查针对单一干扰类型的杂散干扰、阻塞干扰、谐波干扰等展开,对实际场景中由多种干扰源混合构成的混合干扰研究较少。本文围绕TD-LTE网络混合干扰,提出一个集分析排查与解决验证于一身的系统,旨在帮助优化人员快速定位主要干扰源并能有效处理解决问题。     

大气波导对LTE系统内的远端同频干扰分析

进入7月份以后东北某地区TD-LTE系统受到大气波导干扰影响日趋严重,如何及早对大气波导进行预警,并开启干扰抑制功能,降低远端同频干扰,提升网络质量就成为LTE网络发展迫切需要解决的问题.本文研究了大气波导干扰的成因,明确了系统内干扰特征,并选定现网试点完成了干扰抑制功能验证并取得较好效果.     

GSM网络上行干扰的排查及解决方法

在日常的GSM网络优化工作中,上行干扰已经成为影响网络质量的突出问题,然而产生GSM网络上行干扰的原因有很多,不同的原因解决方法会有所不同,这里给出了针对各种原因产生干扰的解决方法,重点介绍了直放站产生的上行干扰.最后对上行干扰的排查流程做了重点分析,给出了优化思路和优化处理方案,帮助快速定位并解决上行干扰,从而优化网络质量、提高用户的感知度、保障移动 GSM 网络畅通运行.     

GSM网络的干扰探讨及优化

随着移动通信业务的迅猛发展,网络的服务质量已经越来越受到用户的关注,如何利用现有的网络设备、资源和容量,最大限度地提高网络的平均服务质量,提高效益,使得网络在不断发展的过程中能够保持网络的服务质量不下降,是我们每一个运维人员的职责。干扰是影响GSM系统通话质量以及掉话率、接通率等网络指标的重要因素。GSM系统受到的干扰有多种,有上行的、下行的干扰,有同频、邻频的干扰,但是总的来说GSM系统的干扰分为三大类即内部干扰、外部干扰和互调干扰,目前由于江西联通内部GSM与CDMA两种制式共存且共站址情况较严重,就更加增加了…     

基站硬件本身上行干扰产生原因及查找方法探讨

文章分析了网络中上行干扰及其对网络的影响，从基站硬件的结构方面阐述了硬件可能产生上行干扰的原因；通过采用高精度仪表对基站硬件参数进行测试，就如何发现和定位基站本身上行干扰作了探讨，并给出了实例，为网络基站上行干扰查找工作提供了参考。     

Implementing interference cancellation to increase the EV-DO Rev A reverse link capacity

This article provides the principles and practice of how interference cancellation can be implemented on the EV-DO Rev A reverse link. It is shown that applying interference cancellation to CDMA achieves the multiple access channel sum rate capacity for either frame synchronous or asynchronous users. The per user SINR gain from space-time interference cancellation translates directly into a CDMA capacity gain of the same factor, allowing EV-DO Rev A to support more users with higher data rates. We demonstrate how interference cancellation can be added to base station processing without modifying user terminals, EV-DO standards, or network coverage. We present commercially viable receiver architectures for implementing interference cancellation with the asynchronism and H-ARQ of EV-DO RevA, and explain why closed loop power control can operate the same way it does today. Network level simulations over a wide range of channels confirm that interference cancellation offers significant capacity gains for all users, while maintaining the same link budget and system stability.     

The impact of network topology on delay bound in wireless Ad Hoc networks

We consider single channel wireless networks with interference constraint among the links that can be activated simultaneously. The traffic flows are assumed to be single hop. Delay performance of the well known throughput optimal maximum weight link scheduling algorithm has been studied recently. In this paper, we study the relation between network topology and delay of maximum weight link scheduling algorithm. First, we consider 1-hop interference model. Under this interference model, an upper bound for the average delay of packets is derived analytically in terms of edge chromatic number of the network graph. Then the results have been extended to the case of general interference model. Under this model of interference, an upper bound for delay as a function of chromatic number of conflict graph is derived. Since chromatic number and edge chromatic number are network topology parameters, the results show that how the upper bound of delay is affected by network topology. Simulation results confirm our analytical relations.     

基于博弈论功率控制的串行干扰消除算法

无线网络实现串行干扰消除算法可以提高网络吞吐量,在采用串行干扰消除算法的无线网络系统中,如何控制节点间传输功率使系统效用最大化是一个NP-Hard难题。针对此问题提出非合作博弈算法来解决节点间的传输功率控制,提出了串行干扰消除算法功率控制的非合作博弈,证明了纳什均衡,所提算法可以获得较高的无线网络吞吐量,仿真实验证实了分析结果并展示了算法的优越性。     

Coverage probability of cellular networks using interference alignment under imperfect CSI

Interference alignment (IA) is well understood to approach the capacity of interference channels, and believed to be crucial in cellular networks in which the ability to control and exploit interference is key. However, the achievable performance of IA in cellular networks depends on the quality of channel state information (CSI) and how effective IA is in practical settings is not known. This paper studies the use of IA to mitigate inter-cell interference of cellular networks under imperfect CSI conditions. Our analysis is based on stochastic geometry where the structure of the base station (BS) locations is considered by a Poisson point process (PPP). Our main contribution is the coverage probability of the network and simulation results confirm the accuracy.     

Optimizing MIMO multipoint wireless networks assuming Gaussian other-user interference

This paper shows how network information theory can lead to practical algorithms for optimizing multipoint wireless networks, whose transceivers are equipped with multiple-antenna elements. Modeling the other-user interference as colored Gaussian noise, it is demonstrated that network capacity can be realized using linear transmit and receive beamforming. Moreover, to optimize the mutual information for all the multiple-input-multiple-output (MIMO) channels, it suffices to consider a much simpler objective function that considers each data link in the network separately, treating all other transmitters as interference. This, in turn, leads to a network objective function, which fully exploits channel reciprocity, exploits MIMO channels, and simplifies the optimization of transmit beamformers across the network. A numerical example is provided showing more than an order of magnitude performance improvement over a conventional network.     

超密集网络中最大化网络吞吐量的预测资源分配

在超密集网络中,小区间干扰严重制约了小区边缘用户的性能体验以及网络吞吐量。无线大数据分析的飞速发展,使得人们有可能通过预测未来的信道状态来分配资源,在无干扰网络中可达到很大的性能增益。但是在干扰网络中如何利用预测信息,在分配资源的同时有效协调干扰还是一个尚未研究的问题。本文分析了干扰网络中预测资源分配的设计难点和存在的问题,针对该问题提出了相应的解决方法,将资源分配建模成一个凸优化问题,通过求解优化问题得到最优的资源分配方法。仿真表明,与未知预测信息的最大化网络吞吐量方法相比,所提方法能够有效提高用户的成功传输率、平均传输进度和网络的吞吐量。当用户数据需求较大时,所提方法可以提供较大的网络性能增益。      

基于4G数据识别5G室内外同频干扰的方案研究

目前中国移动主要基于2.6GHz频端开展5G网络建设,由于室分系统和宏站共用100MHz频谱,因此室内外同频干扰会对5G用户感知产生不利影响。本文提出了一种基于4G测量报告快速识别室外5G高干扰小区的技术方案,可用于识别5G室内外高干扰小区。研究分析和测试验证表明：该方案可快速发现并定位室内外同频干扰覆盖问题,有助于辅助制定网络优化措施。     

Mutual interference considered power allocation in OFDM-based cognitive networks: the multiple SUs case

Power allocation for secondary users (SUs) in cognitive networks is an important issue to ensure the SUs’ quality of service. When the mutual interference between the primary users (PUs) and the SUs is taken into consideration, it is wanted to achieve the conflict-free power allocation while synchronously maximizing the capacity of the secondary network. In this paper, the optimal power allocation problem is considered in orthogonal frequency division multiplexing cognitive networks. The single SU case is primarily formulated as a constrained optimization problem. On this basis, the multiple SUs case is then studied and simulated in detail. During the analysis, the mutual interference among the PUs and the SUs is comprehensively formulated as the restrictions on the SU’s transmission power and the optimization problems are finally resolved by iterative water-filling algorithms. Consequently, the proposed power allocation scheme restrains the interference to the primary network, as well as maximizing the capacity of the secondary network. Specifying the multiple-SUs case, simulation results are exhibited in a simplified scenario to confirm the efficiency of the proposed water-filling algorithm, and the influence of the mutual interference on the power allocation and the system capacity is further illustrated.