Weigui Zhou

A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives.

A novel energy aware dynamic on-off control of base stations in wireless networks

To reduce network energy consumption without losing system performance is a key technique in 5th generation wireless communication systems. The on-off control in multi base stations scenario is proved a mixed dynamic integer programming problem and is hard to be solved. In this work, we provide a novel energy aware dynamic on-off control method in multi-base station scenario to tackle this problem. First of all, we group different base stations in a given area by utilizing the joint correlation of distance and traffic load under the consideration of ideal cooperation; then we perform on-off operations in every group by predicting the upcoming traffic load. Our novel method could reduce the degree of the optimization problem and be processed online with lower complexity. Simulation result indicates that, by using our novel method, we could reduce network energy consumption up to 23% compared to the reference method based on statistical on-off control.

Channel aware spatial constellation design in VLC MIMO communication systems

Visible Light Communication (VLC) has become popular for its feasible and reliable speed and anti-jamming features. In fact, the structure of the transmission system for commercial usage has mainly limited the VLC transmission to downlink. To achieve higher transmission rate, a proper design of transmission constellation should be designed according to channel condition. In this work, we develop a novel design of system constellation in cooperation criterion, by taking the channel state information into account, our proposed novel method has been given in simplified 2 by 2 VLC MIMO scenario with low computing complexity and high performance compared to traditional spatial modulation and repeating coding scheme. The interference from adjacent illuminant could also be decreased. Simulation result indicates that our proposed method could work well compared to other designs, a maximum of 10 times gain has been obtained in some particular conditions.

Mobile Network Security and Privacy in WSN

Abstract This paper discuss the term threats, attacks and vulnerabilities in Wireless Sensor Networks followed by a model that relates the three entities. Based on the model, a framework of Trusted Wireless Sensor node is presented consisting of two major sections which are platform security enhancement and Trusted Authentication protocol to enhance sensor nodes security features and confirm the fidelity of node joining the network respectively. The design of the framework is in line with Trusted Computing Group specifications toward trusted platform implementation. Finally, brief analysis on the proposed framework is presented.

A novel resource allocation in imperfect D2D cooperation in LTE-Advanced Pro systems

The increasing demand on higher transmission speed and lower latency has become popular in 5G related researches. Cooperation is one possible solution to enhance system performance. In this work, we focus on the problem of enhancing the performance of cooperative among mobile terminals under the constraint of cooperative link capacity. Different from traditional researches, we consider the scenario that multiple mobile terminals are working in cooperative mode and the capacity of the link to perform cooperation is limited, which will limit the performance of cooperation. First of all, we establish the scenario and mathematical modeling of the imperfect cooperation among terminals, then we propose a novel sub-optimal centralized method to tackle the problem. A system level simulation result has been given at the end of our manuscript. The result indicates that, the capacity constraint cooperative link will greatly limit the performance of cooperation, by adopting our proposed method, about 7% performance gain could be obtained on average.

Optimal Backhaul Resource Allocation with User Pairing in Uplink Coordinated Multicarrier Networks

With the increasing demand of transmission speed and more robust quality of service, the capacity constrained backhaul gradually becomes bottleneck in cooperative wireless networks, e.g. in Joint Processing mode of LTE-Advanced Pro. This paper focuses the fact of resource allocation with limited backhaul capacity in uplink cooperative networks, where two base stations (BS) equipped with single-antenna each serving multiple users with single-antenna via multi-carrier transmission mode. We propose a novel cooperative scheme based on compress-and-forward with user pairing to solve the problem. To maximize the system capacity under the limited backhaul capacity constraint, we formulate the joint optimization problem of user pairing, subcarrier mapping and backhaul capacity sharing among different pairs (subcarriers). A novel efficient algorithm based on alternating optimization strategy and perfect mapping is proposed to solve this mixed integer programming problem. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul capacity compared with the blind alternatives.

The diagnosis of wired network malfunctions based on big data and traffic prediction: An overview

The increasing demand on higher transmission speed and shorter delay in wired networks becomes critical in recent communication networks. However, the capacity of transmission link is limited by the method of transmission. In this paper, aiming at the situation of large scale networks, an overview of the network optimization based on big data and traffic prediction is given in our proposed work. In wired networks, how to make full use of the transmission bandwidth and provide more reliable QoS is in great demand. Based on the network topology in our facility, we make a summary of current diagnosis method of the network and then propose the future possible way to solve the network malfunction based on big data through network log and complex monitors, then we make an overview of the diagnosis method based on traffic prediction, which could effectively make full use of bandwidth and avoid collision of the network.

Game theoretic approach of a novel decision policy for customers based on big data

In recent days, big data based analysis in hotel industry become popular. Merchants are attracting clients using the accurate analysis of historic data and predicting the behavior of possible clients to perform proper marketing strategy. To study the principle of the game between clients and merchants, in this work, we propose a novel two-stage game theoretic approach of decision policy for clients when choosing the suitable hotel to stay among many candidates, the merchants will provide a non-cooperative game strategy to attract the attention of potential clients. Analysis of the non-cooperative game method based on big data has been given. Simulation results indicate that, by using our proposed novel method, the average price for clients to choose a satisfied hotel is reduced and the successful rate of stay is increased for merchants, which will bring the expected income to a higher level because of the sticky phenomena of users.

Cooperative Downlink Resource Allocation in 5G Wireless Backhaul Network

The 5th wireless communication system will provide higher throughput and more reliable QoS through many key techniques. Cooperation is one possible technology that may provide satisfied performance to users, especially the cell edge users. In this work, we provide the analysis of resource allocation in wireless backhaul networks, through capacity constraint wireless backhaul, the cooperative downlink joint processing is proposed to enhance cell edge performance. We propose the system level simulation and evaluate the cluster performance. Simulation results indicate that the capacity constraint wireless backhaul will bring delay, capacity limit to joint processing method, traditional cooperation scheme will not work well, and our proposed method could gain 13% compared to traditional method.

Energy Oriented Resource Allocation in Heterogeneous 5G Networks

The development of 5G wireless communication systems are changing the daily life. Both transmission speed and Quality of Service (QoS) are developing fast. However, the increasing demand of data traffic brought about the number of base stations, which lead to the additional consumption of system power. Therefore, some of the power consumption is unnecessary by achieving same system performance. In this work, we discuss the resource allocation method in different policies to reduce energy consumption without losing the performance. Both theoretic and system level results are given in this work.