Multiple-input Multiple-output Wireless Sensor Networks Research Articles

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Mobility and Routing based Channel Estimation for Hybrid Millimeter-Wave MIMO WSNs

Recently, technological developments have enhanced, the use of Millimeter-wave (mm-Wave) Multiple Input Multiple Output (MIMO) system in various communication applications and wireless sensor networks as channel estimation efficiency can be immensely improved with the help of this technological developments in Millimeter-wave MIMO system and wireless sensor network as well. Moreover, they can improve quality of communication services to a great extent. However, cell interference in Millimeter-wave (mm-Wave) MIMO system can produce a massive impact on spectral efficiency. Therefore, a Routing Enabled Channel Estimation (RECE) technique is presented in this article to minimize interference between cells. The proposed Channel Estimation technique improves channel capacity as well as spectral efficiency. Moreover, Normalized Mean Square Error (NMSE) is minimized heavily using proposed RECE technique. Here, main aim of this article is to reduce cell interference and channel estimation inside a cell by using route selection, beam selection, and spatial frequency estimation. Here, different scenarios and parameters are considered to evaluate performance efficiency of proposed RECE technique in terms of spectral efficiency, NMSE and SNR and compared against varied traditional channel estimation techniques. Moreover, it is clearly evident from performance results that the proposed channel estimation technique performs better than the other two methods.

Design of Cooperative MIMO Wireless Sensor Networks With Partial Channel State Information

Wireless sensor networks (WSNs) play a key role in automation and consumer electronics applications. This paper deals with joint design of the source precoder, relaying matrices, and destination equalizer in a multiple-relay amplify-and-forward (AF) cooperative multiple-input multiple-output (MIMO) WSN, when partial channel-state information (CSI) is available in the network. In particular, the considered approach assumes knowledge of instantaneous CSI of the first-hop channels and statistical CSI of the second-hop channels. In such a scenario, compared to the case when instantaneous CSI of both the first- and second-hop channels is exploited, existing network designs exhibit a significant performance degradation. Relying on a relaxed minimum-mean-square-error (MMSE) criterion, we show that strategies based on potential activation of all antennas belonging to all relays lead to mathematically intractable optimization problems. Therefore, we develop a new joint relay-and-antenna selection procedure, which determines the best subset of the available antennas possibly belonging to different relays. Monte Carlo simulations show that, compared to conventional relay selection strategies, the proposed design offers a significant performance gain, outperforming also other recently proposed relay/antenna selection schemes.

Precoder design for decentralised estimation over MIMO‐WSN based on stochastic models

New precoder matrices are designed to estimate an unknown vector parameter considering stochastic channels for multiple-input multiple-output wireless sensor network (MIMO-WSN) with decentralised sources. Two types of WSNs are considered, with and without total power network limitations. Within this context, two closed-form relations are derived for the precoder matrices and mean square error (MSE) of the unknown vector parameter is obtained. To cancel any operations at a fusion centre to estimate the aforementioned parameter, a distortionless constraint is added. In simulation section, the authors compare the MSE performances of the proposed method in stochastic MIMO channels with those in deterministic MIMO channels. The simulation result indicates that the MSE performance in the stochastic channels is decreased by almost 1.3 dB at low signal-to-noise ratios. Therefore, the reliability of the unknown vector parameter estimation is enhanced using the MIMO model. Ultimately, effects of bandwidth and number of sensor nodes on the MSE criterion are also analysed.

Data Transmission Strategy for Wireless Sensor Network Based on Vir-tual MIMO

Virtual multiple input multiple output (MIMO) technology has been widely researched in the aspect of energy conservation for wireless sensor network (WSN) communication. In this this paper, data transmission for the entire network based on virtual MIMO WSN structure is studied, combined with clustering and multi-hop transmission mode. Each cluster head (CH) is formed according to the clustering algorithm, and the data is transmitted to the adjacent CH by cooperative communication mode. The circuit energy consumption and the transmission energy consumption are both considered in our model, so the minimum inter-cluster transmission energy consumption is obtained, and the optimal path to the sink node is obtained. The proposed strategy does not need the receiver’s collaboration to avoid the complexity of the receiver; meanwhile more energy consumption of the network is saved from the perspective of the network life cycle. The simulation results show that the proposed strategy can reduce more energy consumption and prolong the network life cycle.

Review of the Book “Advanced Cognitive Radio Network”

Chapter 1 History and foundation by Alagan Anpalagan. This book chapter deals with history and foundation of cognitive radio. In recent years wireless communications have experienced an unprecedented success for the rapidity of their diffusion and for their impact in the life of human society. The technologies used in wireless communications are far from being mature and many changes induced by their progress are still to come. Cognitive radio is one of these technologies and is regarded as a key technology to increase efficiency in wireless communications. In many circumstances the spectrum assigned to wireless communications is not fully used. The main goal of cognitive radio is to improve the exploitation of the spectrum. The idea is to let the unlicensed users to access the spectrum left unused by the licensed users. In this chapter the main steps of the brief history of cognitive radio are presented including issues related to policy regulations that have influenced the technology and alternative technical solutions as software defined radio. The chapter ends with a brief discussion of future applications in wireless communications and of the challenges that they pose to cognitive radio. This is a well written and informative chapter that deals with an important technology. I suggest to read it. Chapter 6 MIMO systems and cooperative networks performances by Kosai Raoof, Maha Ben Zid. This chapter deals with MIMO (Multiple Input Multiple Output) systems. This is a technology used to in wireless communications to improve transmission robustness and to increase spectral efficiency. The relation between MIMO systems and wireless sensor networks is investigated. Spatially distributed wireless sensor networks are deployed for many different purposes, let us mention, for example, environment monitoring missions or surveillance missions. Cooperative networks with virtual MIMO channels are studied, in particular networks aware of their environment are considered. These are cognitive networks that operate in wireless form. This last feature is the bridge that links them to cognitive radio. In fact the cognitive radio technology is used to allocate spectrum to the users of the cognitive network in an adaptive way. This book chapter deals with a specific application, however, this is a very important application and this work is written in a way that makes it readable by a wide audience technically oriented readers. I suggest to read it.

Editorial for WICON 2010 on “Recent advances in wireless internet”

Networks and Applications (MONET). This special issue is devoted to the topic of the latest research and development on wireless Internet. Wireless Internet is quickly emerging as a reality, thanks to the fast evolution of many wireless access technologies. Convergence of heterogeneous wireless networks and the next generation Internet further brings wireless Internet into a variety of application scenarios which provide mobile users with a wide range of highly demanding services, such as high speed data and real-time multimedia delivery. On the other hand, it is of critical importance to obtain a fundamental understanding of wireless Internet architectures and explore new services and solutions in order to achieve the ultimate goal of wireless Internet access anytime anywhere The aim of this special issue is to present a collection of high-quality research papers that report the latest research advances in wireless Internet communications, networks, systems, services, and applications. The whole special issue includes the extended papers in the 5th Annual International Wireless Internet Conference (WICON 2010), which was held in March 2010 (http://www. wicon.org/2010/). In this special issue, we selected 6 papers. The selected papers covered the following important topics in the field of wireless Internet: cognitive radio, wireless sensor networks, multimedia communications, and vehicular networks. A detailed overview of the selected works is given below. The first paper, Joint Spectrum Allocation and Relay Selection in Cellular Cognitive Radio Networks, presents a cross-layer framework that jointly considers spectrum allocation and relay selection with the objective of maximizing the minimum traffic demand of secondary users in a cognitive radio network cell. This cross-layer design problem is formulated as a Mixed Integer Linear Programming (MILP) and a low complexity heuristic algorithm is proposed to solve the problem. In addition, a spectrum allocation is studied among several cells with the objective of maximizing the overall minimum throughput of all cells while ensuring each individual cell’s minimum throughput requirement. The second paper, Joint Optimization of Power, Packet Forwarding and Reliability in MIMO Wireless Sensor Networks, investigates the reliable packet forwarding in Wireless Sensor Networks (WSNs) with the multiple-input multiple-output (MIMO) and orthogonal space time block codes (OSTBC) techniques. The objective is to propose a cross-layer optimized forwarding scheme to maximize the Successful Transmission Rate (STR) while satisfying the given end-to-end power consumption constraint. The channel coding, power allocation, and route planning are jointly considered to significantly improve the transmission quality in terms of STR. The joint optimization design is Y. Zhang (*) Simula Research Laboratory and University of Oslo, Oslo, Norway e-mail: yanzhang@simula.no

Joint Optimization of Power, Packet Forwarding and Reliability in MIMO Wireless Sensor Networks

In this paper, we study the reliable packet forwarding in Wireless Sensor Networks (WSNs) with the multiple-input multiple-output (MIMO) and orthogonal space time block codes (OSTBC) techniques. The objective is to propose a cross-layer optimized forwarding scheme to maximize the Successful Transmission Rate (STR) while satisfying the given end-to-end power consumption constraint. The channel coding, power allocation, and route planning are jointly considered to significantly improve the transmission quality in terms of STR. The joint optimization design is formulated as a global deterministic optimization and also a local stochastic optimization issues. It is found that the stochastic optimization approach can effectively model, analyze, and solve the routing problem. In order to substantially reduce the implementation complication of the global optimization, we propose a low-complexity distributed scheme. The determination of relaying nodes and power budgets are decoupled, i.e. performing route planning and power allocation separately. We have shown that the result in the distributed scheme is able to provide sufficiently accurate predication of the global optimization. In addition, the proposed scheme can clearly reduce the Symbol Error Rate (SER) and achieve higher STR compared with two existing energy-efficient routing protocols, in which no joint design is considered.