Wenjing Li

WCDMA KPI framework definition methods and applications

With the development of the commercial applications of WCDMA in the whole world, the comprehensive and scientific measurement and assessment of network performance for WCDMA have become one of the urgent requirements for operators. KPI is always a significant assessment standard for network performance from the 2nd wireless communication. As the KPI/KQI assessment architecture is proposed by TMF and the End-to-End QoS/QoE has become one of the research focuses, KPI is therefore rapidly becoming a indispensable factor in the assessment architecture of WCDMA. Due to the lack of definition framework and methods for KPI, it is difficult for the existing network performance KPI to cover all importance aspects of network and to make fair evaluation of network performance. In response to these needs, this paper proposes a definition methodology composed of the definition criteria, the assessment framework, and the weight division principles for WCDMA KPI. Besides, it also illustrates the measurement and assessment processes of network performance KPI of WCDMA by the practical application experience of Chinese operators.

A Social-Aware Resource Allocation for 5G Device-to-Device Multicast Communication

With the ever-increasing demands for popular content sharing among humans, device-to-device (D2D) multicast communication, as a promising technology to support wireless services within a local area, is introduced in a 5G cellular network. However, the existing resource allocation approaches for D2D multicast communication usually consider only physical domain constraints but neglect social domain factors, which would result in ineffective D2D links between users unwilling to share interests. Different from existing works, the D2D multicast scheme proposed in this paper will produce effective D2D multicast links by sufficiently utilizing both the physical and social properties of mobile users, with the goal to maximize the throughput of the overall social-aware network and guarantee fairly allocation of the channel between different D2D multicast clusters. The scheme mainly consists of two parts, the formation of D2D multicast clusters and joint optimization of power and channel allocation. In the formation of D2D multicast clusters, members and head in each cluster are selected by taking into account both social attributes and physical factors, such as community, ties, and geographical closeness. In the joint optimization, a two-step scheme is designed to first calculate the optimal power allocation by geometric proximity and then select suitable cellular channels for each D2D multicast cluster utilizing an extended one-to-many bipartite graphs matching algorithm. Simulation results demonstrate that, compared with heuristic algorithm and stochastic algorithm, the proposed scheme can increase the throughput of the overall social-aware network by about 5% and 50%, respectively.

Benders Decomposition-based video bandwidth allocation in mobile media cloud network

Due to the fast growth of wireless multimedia applications, mobile media cloud network is getting more and more popular. In the architecture of mobile media cloud network, the wireless access points are placed on edge of the cloud to provide media services for the mobile users. The video bandwidth allocation managed by a centralized media cloud directly affect the user’s experiences. In this paper, the problem of the video bandwidth allocation in the mobile media cloud access network is explored. Firstly, this paper formulates the problems in bandwidth allocation in the form of quadratic programming in order to maximize the system revenue on the basis of video bitrates capacity between the user and the Mobile Access Edge Point (MAEP). The optimization model could more vividly explicate the trade-off between the expected bitrates capacity and the allocation fairness of User Equipment (UE). Then this paper subdivides the problem into major and minor ones and proposes an algorithm based on Benders’ Decomposition to deal with it. The optimality of the solution is proved by both theoretical and experimental investigations. The error tolerance is analyzed as the algorithm disavows the trade-off between the convergence time and the system performance. The experiments show that the average computing time and confidence interval of the proposed algorithm are lower than Simplex algorithm by 68% and 94% and Barrier algorithm by 46% and 75% respectively at most. Finally, some conclusions are derived from evaluations on the system performance against various network topologies and different values for parameters of the proposed algorithms.

Modeling and optimization of self-organizing energy-saving mechanism for HetNets

Energy efficiency in future green cellular wireless networks poses a challenge to operators and researchers. An effective method of providing energy savings (ES) in base stations (BSs) is to switch off idle BSs or put them into sleep mode and subsequently migrate the traffic loads to active BSs in their neighborhood. The intrinsic issue related to such methods applied to heterogeneous networks (HetNets) is that the optimal selections of various types of BSs during both energy-saving and coverage-compensating (CC) processes are difficult to determine. In an attempt to resolve the insufficiency of existing strategies, we propose a novel traffic-aware self-organizing ES mechanism that enables efficient resource allocation and interference management in multi-level networks. To further develop optimal energy conservation procedures for BSs, a new constraint model is proposed. We employ coverage gaps and over-provisioning as the optimization objectives and analyze the effects of their weights. The performance in terms of energy savings is evaluated in an urban Long-Term Evolution (LTE) scenario with different types of BSs. The simulation results show that the proposed mechanism can maximize energy efficiency in heterogeneous cellular networks while guaranteeing the quality of service. This algorithm is autonomous in terms of decision making and execution.

Self-Organized Cell Outage Detection Architecture and Approach for 5G H-CRAN

An attractive architecture called heterogeneous cloud radio access networks (H-CRAN) becomes one of the important components of 5G networks, which can provide ubiquitous high-bandwidth services with flexible network construction. However, massive access nodes increase the risk of cell outages, leading to negative impact on user-perceived QoS (Quality of Service) and QoE (Quality of Experience). Thus, cell outage management (COM) became a key function proposed in SON (Self-Organized Networks) use cases. Based on COM, cell outage detection (COD) will be resolved before cell outage compensation (COC). Currently few studies concentrate on COD for 5G H-CRAN, and we propose self-organized COD architecture and approach for it. We firstly summarize current COD solutions for LTE/LTE-A HetNets and then introduce self-organized architecture and approach suitable for H-CRAN, which includes COD architecture and procedures, and corresponding key technologies for it. Based on the architecture, we take a use case with handover data analysis using modified LOF (Local Outlier Factor) detection approach to detect outage for different kinds of cells in H-CRAN. Results show that the proposed approach can identify the outage cell effectively.

Resource Allocation for Reliable Communication Between Controllers and Switches in SDN

In software-defined networking (SDN), the communication between controllers and switches is very important, for switch can only work by relying on flow tables received from its controller. Therefore, how to ensure the reliability of the communication between controllers and switches is a key problem in SDN. In this paper, we study this problem from two aspects: the controller placement and the resource backup aspect. Firstly, in order to implement the reliable communication and meet the required propagation delay between controllers and switches, a min-cover based controller placement approach is proposed. Then, in order to protect both controllers and control paths from regional failure, a backup method based on an exponential decay failure model is proposed, which considers the regional influence and the survivability of backup controllers and control paths. Simulations show that our controller placement approach can meet the reliability and delay requirement with appropriate controller allocation scheme, and our backup method can improve the survivability of backup controllers and control paths while ensuring the performance of control network.

Risk analysis and optimization for communication transmission link interruption in Smart Grid cyber-physical system:

Since the communication network of the cyber-physical power system is responsible for communicating information, which guarantees the operation of the cyber-physical power system, researchers focus on the stability of the communication system. This article analyzes the risk of the communication transmission link interruption based on the network structure and characteristics of service transmission and proposes a path optimization method. First, we analyze the impact of link disruption on network structure and service, respectively, and quantify the impact as link interruption risk. According to the risk analysis, we propose an optimization method utilizing the Dijkstra’s algorithm and the genetic algorithm to reconfigure service paths, which aims to minimize time delay and realize the equilibrium of service distribution. Through a particular situation, we calculate the link interruption risk and use the optimization method to configure service path for affected service. The results show that the time delays of the optimized service paths are in the acceptable level as well as the balance index of the service distribution is decreased obviously. The simulation experiment reveals the operability of the risk analysis method and the effectiveness of the path optimization method, which provides a technical reference for risk analysis and service path configuration.

Gain-Aware Joint Uplink-Downlink Resource Allocation for Device-to-Device Communications

This paper proposes a novel Gain-Aware Uplink-Downlink(GAUD) jointly resource allocation scheme to maximize the Device-to-Device(D2D) throughput while guaranteeing Quality of Service (QoS) of cellular users. We formulate the global optimization problem as a mixed integer nonlinear programming problem and decompose it into three sub-problems. Firstly, a method of jointly uplink and downlink reuse mode selection is proposed. Based on the throughout gain, each D2D pair is appropriately assigned by either downlink or uplink frequency resource to reuse. Then a heuristic scheduling is designed for fairness channel allocation in order to form D2D users as much as possible. At last, the Lagrangian dual algorithm is developed to solve the optimal power allocation. The simulation results show that our proposed jointly downlink-uplink resource reusing scheme can make the system throughput increased by about 35% and 50% higher than the scheme based on Only Downlink and Only Uplink resource reusing.

Preventing Congestion by Selective Admission Control in LTE-Based Public Safety Network

LTE-based Public Safety Network (PSN) is a wireless communication network which can provide efficient and reliable communication in disasters or emergencies for disaster relief and public protection. Therefore, ensuring that network congestion will not happen in PSN during an emergency is becoming increasingly important. LTE-based PSN is easy to be congested because part of spectrum resources is compressed to guarantee priority requirements of public safety users. In this paper, we develop a new method namely Selective Admission Control (SAC) mechanism to manage the radio bearers access to the commercial radio for Public Safety (PS) in LTE-based PSN. In the case of emergency, we select the traffic bearer with minimum estimated load increment accessing to the LTE-based PSN. The channel quality of new bearers should be taken into account, which means that in congestion, users who arrive earlier with poor channel quality will be rejected to reserve sufficient resources for users who arrive later with good channel quality. The simulation results show that the SAC mechanism can improve throughput by 36% and lower the rejection rate by 73% at most than reference method based on non-selective access control model, as a result effectively avoiding the network congestion and improving the utilization of spectrum resources for public safety communication.

Sharing data store and backup controllers for resilient control plane in multi-domain SDN

software-defined networking (SDN) uses a centralized control plane to manage the whole network. If the scale of the network is large, it is necessary to divide it into multiple domains. Since the network scale becomes larger, the probability of failure occurrences is higher. Therefore, it is important to guarantee the control plane resilience in multi-domain SDN. However, the existing approaches cannot store the network state in real time, and do not consider the backup controllers placement problem in multi-domain SDN. In order to ensure the resilience of the control plane in multi-domain SDN, we propose a sharing data store and backup controllers based approach. Sharing data store is used to ensure that each master controller has a view of the whole network and data store can save the network state during the failure time. The sharing backup controllers are used to guarantee the resilience of control plane with minimum cost. Simulations show that our approach can use as less backup controllers as possible to ensure the resilience of control plane.