Zunwen He

The Role of Large-Scale Fading in Uplink Massive MIMO Systems

In this paper, we analyze the ergodic achievable rate of a large uplink multiuser multiple-input-multiple-output (MU-MIMO) system over generalized-

An Energy Consumption Balanced Clustering Algorithm for Wireless Sensor Network

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Analysis of Key Technologies for Cognitive Radio Based Wireless Sensor Networks

fading channels. In the considered scenario, multiple users transmit their information to a base station equipped with a very large number of antennas. Since the effect of fast fading asymptotically disappears in massive MIMO systems, large-scale fading becomes the most dominant factor for the ergodic achievable rate of massive MIMO systems. Regarding this fact, in our work, we concentrate our attention on the effects of large-scale fading for massive MIMO systems. Specifically, some interesting and novel asymptotic expressions of ergodic achievable rate have been derived with both perfect channel state information (CSI) and imperfect CSI. Simulation results assess the accuracy of these analytical expressions.

An energy-efficient adaptive clustering routing algorithm for wireless sensor networks

LEACH (Low Energy Adaptive Clustering Hierarchy) is a clustering-based protocol that utilizes randomized rotation of the cluster-heads to evenly distribute the energy load among the sensor nodes in the network. This classical protocol has been widely used in wireless sensor network (WSN). However, it has the disadvantage of irrationality of electing cluster-head and of unbalanced energy consumption of nodes. Based on the energy factor introduced in the cluster-head-electing threshold in LEACH, by optimizing the election probability of cluster-head, an improved energy consumption balanced algorithm LEACH-EP is proposed. The simulation results show that the proposed algorithm can balance energy consumption of nodes and prolong the lifetime of network.

A grid-based energy efficient routing protocol in Wireless Sensor Networks

Wireless sensor networks (WSNs) currently operate in the unlicensed industrial, scientific and medical (ISM) spectrum band. However, more and more wireless equipments make this band overcrowded. The tremendous growth in the applications of WSNs has posed great challenges for the precious radio electromagnetic spectrum resource. The limited wireless spectrum resource will be the bottleneck for the large-scale popularization of WSNs. By contrast, the utilization rate of licensed spectrum is very low, and some bands are actually never occupied. It is promising and also challenging for WSNs to adopt the cognitive radio (CR) technology to sense spectrum hole and utilize the vacant frequencies to improve the spectrum utilization rate and communication validity. On the basis of detailed analysis of the involved key technologies for CR-based WSNs, the related solutions are introduced. In addition, a new hardware structure of sensor node is proposed and energy-saving design strategies are discussed.

Design of monitor system for grain depots based on wireless sensor network

An energy-efficient adaptive clustering routing algorithm (EEACRA) for wireless sensor networks was proposed, in order to overcome the drawbacks with the cluster heads in LEACH, such as over-accumulated energy consumption, irrational distribution, none-optimal proportion, etc. EEACRA made several improvements. First, the node with more energy had more chances to become a cluster head by introducing the energy-weighted factor and energy decision condition in cluster head electing threshold. Second, the energy-weighted delay strategy involved in cluster head broadcasting phase optimized the cluster heads distribution and decreased the collision probability. Third, the introduced mechanism of minimum energy cost multi-hop routing reduced the energy consumption of cluster heads. The simulation results show that the EEACRA can not only effectively balance the whole network energy consumption, but also prolong the network lifecycle.

Design of automated test system based on GPIB

Due to limited energy of Wireless Sensor Networks (WSNs), routing plays a crucial role in improving energy efficiency. The low-energy adaptive clustering hierarchy (LEACH) protocol is a classical solution to cut down energy cost, but it neglects residual energy of sensor nodes and long-range communication which causes low network coverage and high energy consumption. To avoid these shortcomings, we put forward a grid-based energy efficient routing protocol (GEERP) which focuses on three improvements: energy consumption, energy efficiency and network coverage. In GEERP, WSNs are divided into two levels: one is called secondary level grid (SG), which is formed by one cluster head (CH) and several cluster members (CMs); the other one is premier level grid (PG), which consists of nine adjacent SGs. In each round, CH is selected based on residual energy level of sensor nodes in a cluster. Then fused data of CH will be transmitted to sink node through multi-hop routing which is determined by minimum weight. Simulation results demonstrate that GEERP can not only balance network energy consumption of network but also can highly improve the network coverage.

A new data gathering scheme for trajectory constrained mobile sink in WSN

The safety of grain storage is a significant thing that concerns peoples living quality and national economic development. It is exceedingly important for manager to timely master the grain storage condition. Improving the automation level of monitor system is the key to assure the safety of grain storage. A novel scheme of monitor system designed for grain depots is proposed based on wireless sensor network (WSN). This scheme utilizes sensor nodes deployed in barns, which compose an autonomous network, to collect environmental data of grain storage and then transmit them to remote control center by means of wireless and multi-hop communication. Due to using small, low cost sensor nodes and wireless communication, several problems in traditional monitor system are solved. These problems include large cable coverage, more opportunities of interference and lighting strike, high maintenance cost and so on. Consequently, the WSN-based system has good reliability, maintainability and cost effectiveness.

Fuzzy evaluation algorithm for system effectiveness of wireless sensor networks

The general purpose interface bus (GPIB) designed initially by Hewlett-Packard is the first standard communication protocol between instruments and computers, and is recognized as an IEEE standard. This paper introduces the general architecture using GPIB to integrate several functionally different instruments as an automated test system (ATS). After that, based on a practical case, a design of the ATS used for testing electrical performance index of microwave transceiver is presented, including the key technologies and the methodology developed for this design.

An Introduction to Hyper-Complex on Meaningful Digital Watermarking

The advantages of deploying mobile sinks (MSs) in wireless sensor networks (WSNs) have attracted tremendous attention recently, because mobility of a sink provides an efficient method to improve data gathering performance in WSNs. However, in such kind of WSN, the efficiency of data dissemination is obviously affected by the trajectory of the MS. Therefore, optimal moving schemes of the MS have been studied in many researches. Nevertheless, in many cases, the trajectory of the MS is not able to change ideally as previous studies assumed but depending on the environmental conditions. In this paper, we focus on the efficiency of data gathering in WSN with a MS whose trajectory cannot change ideally and propose a new data diffusion scheme - implementing a new Pre-Diffusion Algorithm (PDA) in a hierarchical WSN aimed at improving data gathering efficiency. This hierarchical WSN is composed of several clusters, and datatransmission is done by higher powered cluster head (CH) node. Our scheme predetermines the cluster area where the MS is going to arrive in most probability in next period of time. MS fulfills data converging in the cluster head (CH)whose distance to the MS may the smallest compared with other CHs when data gathering starts. Thus more data can be collected with less trajectory length of MS. Simulation results show that our proposed scheme improves data gathering efficiency as compared to conventional scheme.