A Multi-Cluster-based Distributed CDD Scheme for Asynchronous Joint Transmissions in Local and Private Wireless Networks
Abstract : In this paper, a multiple cluster-based transmission diversity scheme is proposed for asynchronous joint transmissions (JT) in private networks. The use of multiple clusters or small cells is adopted to reduce the transmission distance to users thereby increasing data-rates and reducing latency. To further increase the spectral efficiency and achieve flexible spatial degrees of freedom, we consider that a distributed remote radio unit system (dRRUS) is installed in each of the clusters. A key characteristic of deploying the dRRUS in private networks is the associated multipath-rich and asynchronous delay propagation environment. Therefore, we consider asynchronous multiple signal reception at the remote radio units and propose an intersymbol interference free distributed cyclic delay diversity (dCDD) scheme for JT to achieve the full transmit diversity gain without requiring full channel state information of the private network. The spectral efficiency of the proposed dCDD-based JT is analyzed by deriving a new closed-form expression, and then compared with link-level simulations for non-identically distributed frequency selective fading over the entire network. Due to its distributed structure, the dRRUS relies on backhaul communications between the private network server and cluster master (CM), which is the main backhaul connection, and between the CM to remote radio units, which are the secondary backhaul connections. Thus, it is important for us to investigate the impact of reliability of main and secondary backhaul connections on the system. Our results show that the resulting composite backhaul connections can be accurately modeled by our proposed product of independent Bernoulli processes.
? It is the process of acquiring an object or user’s location through intelligent devices (sensors) in an indoor or outdoor environment.
? However, there exist numerous challenges in the development of such IoT applications.
? It is clear that most of the existing surveys target a particular localization domain, i.e., outdoor or indoor.
? IoT is an extension of the Internet that envisions connecting all daily devices to the Internet for communications through interactions or sensing devices.
? These sensing devices are connected to form a network, termed a wireless sensor network (WSN).
? Network coverage is one of the issues in WSN and directly related to localization performance.
? When a plurality of BSs transmit simultaneously, the existence of interference is an intrinsic problem as well.
? The rapid increase in cybersecurity challenges and lack of standardization for basic privacy mechanisms make it an open research problem .
? Various classification algorithms, such as support vector machines (SVM), decision trees (DT), and neural networks offer the potential to resolve this problem.
? Therefore, energy consumption is one of the core issues in terms of smart environment and localization.
• The proposed technique develops a belief function by combining fingerprint based target observation and evidence associated with sensor mobility to improve the accuracy of target tracking.
• Therefore, this paper explores the recently proposed localization schemes in IoT.
• The proposed solution is energy efficient, reasonably accurate and reliable in terms of target tracking.
• The proposed scheme results in the tracking of dynamically changing unknown numbers of targets in urban areas.
• The proposed algorithm simplifies the set-up phase time of the network resulting in reducing the overhead of the network.
? A private network is a promising new connectivity model offering previously unavailable wireless network performance to businesses and individuals.
? Potential applications to industries, businesses, utilities, and public sectors have gravitated towards 5G wireless networks with increasingly stringent performance requirements, in terms of availability, reliability, latency, device density, and throughput.
? We denote the analytically derived SE by An, whereas we denote the exact performance metric obtained by the link-level simulations by Ex in the sequel.
? To increase the spectral efficiency and coverage, and to achieve flexible spatial degrees of freedom, a distributed remote radio unit system (dRRUS) is installed in each of the clusters.
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