M-ary相位偏移鍵(M-PSK)適應性調變在合作性無線中繼網路之最佳中繼點選擇演算法

This chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance.

Multiple input multiple output (MIMO) relay networks are wireless communication systems comprising of multiple nodes, each of which is equipped with multiple antennas. Information theories have shown that using multiple nodes to simultaneously relay a message can improve the capacity of source-to-destination communications. In this paper, we propose new relaying schemes for MIMO relay networks. The major concept behind the proposed schemes is to transform each of the MIMO relay channels into an equivalent triangular channel with positive real diagonal entries. By doing so, the resultant MIMO relay channel can simultaneously offer both distributed array gain (diversity gain obtained among relay nodes) and intranode array gain (diversity gain realized by multiple antennas of individual relay node) while maintaining the maximum spatial multiplexing gain (number of parallel data pipes). Based on this concept, three relaying schemes are derived that perform QR decomposition and phase control. Numerical results confirm that at least one of the proposed schemes outperforms the amplify-and-forward and the zero-forcing relaying schemes under various conditions. Moreover, we show that ratios of noise power level at relay and destination node have a great impact on capacities.

This paper analyzes the performance of cooperative amplify-and-forward (CAF) relay networks that employ adaptive M-ary quadrature amplitude modulation (M-QAM)/M-ary phase shift keying (M-PSK) digital modulation techniques in Nakagami-m fading channel. In particular, we present and compared the analysis of CAF relay networks with different cooperative diversity and opportunistic routing strategies such as regular Maximal Ratio Combining (MRC), Selection Diversity Combining (SDC), Opportunistic Relay Selection with Maximal Ratio Combining (ORS-MRC) and Opportunistic Relay Selection with Selection Diversity Combining (ORS-SDC). We advocate a simple yet unified numerical approach based on the marginal moment generating function (MGF) of the total received SNR to compute the average symbol error rate (ASER), mean achievable spectral efficiency, and outage probability performance metrics.

Closed form expressions for the bit error rate (BER) for a multiple input multiple output (MIMO) relay system employing maximum likelihood (ML) based decode and forward (DF) cooperative diversity are obtained. The DF operation at the relay involves maximal ratio combining (MRC) on the source-relay link and space-time coding (STC) on the relay-destination link. Exact expressions of the BER are obtained for the case of a single relay supporting two antennas. For a system employing a large number of relays, each having two antennas, approximate expressions for the BER are obtained using the piecewise linear (PL) approximation for the ML detector. This is done by finding the statistics of conditionally Gaussian random variables, that appear in the decision variable. The validity of the analytical expressions is then verified through simulations. Through numerical results obtained from the BER expressions for large number of relays, it is then shown that the loss in diversity order due to DF can be compensated by using multiple antennas at the relay.

A multiple-input multiple-output (MIMO) relay network is composed of source, relay, and destination nodes, each of which is equipped with multiple antennas. Network information theory has shown that the use of multiple relay nodes in source and destination (S-D) communication makes the capacity of the S-D system logarithmically increase with the number of relay nodes. In [13], we proposed a MIMO relay scheme for a relay network with single source and destination pair; each of the multiple relay nodes performs QR decomposition of backward and forward channels in conjunction with phase control (QR-P-QR). In this paper, we extend this scheme to the MIMO relay network with multiple source and destination pairs. For this aim, we use the group nulling approach to decompose the multiple S-D MIMO relay channel to parallel independent S-D MIMO relay channels, and apply the QR-P-QR scheme in each of the decomposed MIMO relay links. Numerical examples show that the proposed relay scheme offers higher capacity than the existing zero-forcing (ZF) relaying scheme

Transmission collision is one of the main reasons of performance degradation in dense wireless sensor networks (WSNs). Transmission collision can cause throughput reduction, excessive delay and packet loss. One of the methods to minimize the probability of packet collision is the reduction of the collision area (area around sending nodes where collision may take place). In this study we investigate the problem of collision probability minimization through the use of cooperative transmissions and optimal power allocation in WSNs. We formulate the problem as a constrained optimization problem subject to an outage probability constraint. We determine the optimal transmission power of the source and the relay nodes which minimizes the collision area. Results show that the proposed technique significantly reduces the collision area while keeping the outage performance below the targeted value. Results also show that the proposed technique outperforms the direct transmission system as well as the cooperative system with equal transmission power.

A Wireless Sensor Network (WSN) normally consists of an exceptionally large number of inexpensive, disposable, robust, small, and low power sensor nodes operational considerately. A Distributed and Scalable Scheduling Access (DSSA) scheme that mitigates in wireless sensor networks handles some mobility with high data loss due to the faults. A virtual grid network in distributed and scalable scheduling access scheme is an effortless method to cluster local sensors but fails in network scalability improvement. Existing, Information Controlled Transmission Power (ICTP) alteration method uses higher transmission powers with additional information than individuals that are less instructive to distribute their object state information with the neighboring nodes. ICTP does not detect faults and outlier sensor nodes in the network and probable safety measures have to be taken against them. To overcome these faulty and energy saving issues, Collaborator Homed Routing (CHR) mechanism is developed in WSN. In CHR, cluster heads aggregate information and relay information to the base station independently for improving system’s transmission power with half amount of energy consuming. Non Cluster Head (NCH) nodes choose a restricted number of objects in the information transmission. Based on the CHR principles, designed and implemented a novel mechanism to handle faulty situations. Using CHR in WSN, cluster head faults are installed to observe the scalability of these mechanisms. Therefore CHR consumes less energy with minimal faults. Experimental results show that proposed routing considerably reduces energy consumption, fault free routing, and reduces the possibility of communication disturbance, network scalability, throughout and link failure ratio is compared to existing method

Internet of Things (IoT) is the paradigm used nowadays to summarize what is expected form the fourth industrial revolution (Industry 4.0) that is the connectivity of a huge number of “smart” objects disseminated in dissimilar scenarios. This concept is foreseen for practically any possible application domain: from home to transportation, from industry plants to health care, and for space monitoring. Long-term and self-sustainability of these smart thinks (people, objects, tools, etc.) becomes the most relevant aspect for the implementation of such a complex vision. In this framework, my PhD activities have been concentrated. The common goal is to investigate advanced solutions for energy-aware systems and circuits cooperating to enable the IoT paradigm. In particular, I have studied, designed and experimentally demonstrated quite a few novel solutions able to overcome some of the energy limitations existing in IoT. The first project I have developed is an energy-autonomous power relay node at 2.45 GHz that is able to harvest energy from ambient-available or from dedicated RF sources and either use it for operating the node or for supplying power to other nodes. Both a hybrid and a monolithic implementation of the relay system have been implemented. Then I was dedicated to the design of a system enabling Wake-Up Radio (WuR) operation at ultra-low power. The ambitious goal of WuR radios is to reduce the communication power consumption in Wireless Sensor Networks (WSN) and IoT. With this scope in mind, I have proposed and implemented a multi-band WuR architecture. The flexibility of using frequency diversity in WuR enables a more reliable and robust communication channel. From the source side, analytical and experimental studies have been carried out to define the optimum Power Optimized Waveform (POW) excitation to push the WuR sensitivity down to power as low as -65 dBm.

The relay node placement problem in wireless sensor network (WSN) aims at deploying the minimum number of relay nodes over the network so that each sensor can communicate with at least one relay node. When the deployed relay nodes are homogeneous and their communication ranges are circular, one way to solve the WSN relay node placement problem is to solve the minimum geometric disk cover (MGDC) problem first and place the relay nodes at the centers of the covering disks and then, if necessary, deploy additional relay nodes to meet the connection requirement of relay nodes. It is known that the MGDC problem is NP-complete. A novel linear time approximation algorithm for the MGDC problem is proposed, which identifies covering disks using the regular hexagon tessellation of the plane with bounded area. The approximation ratio of the proposed algorithm is (5+ϵ), where0<ϵ≤15. Experimental results show that the worst case is rare, and on average the proposed algorithm uses less than 1.7 times the optimal disks of the MGDC problem. In cases where quick deployment is necessary, this study provides a fast 7-approximation algorithm which uses on average less than twice the optimal number of relay nodes in the simulation.

For energy-constrained wireless sensor networks (WSNs), the topology control issue is fundamental and important to maximize the overall network lifetime. Recently a two-tiered network model has been proposed for this purpose. It is a cluster-based network model composed of application and sensor nodes. In this model the application nodes are easy to run out of energy because they not only serve as cluster heads for aggregating data packets from the sensor nodes in their clusters but also are responsible for forming a connected network topology for information dissemination at the higher tier. In order to balance nodes' power consumption and extend the topological lifetime of a WSN with regard to a certain amount of initial energy provision, we propose a logical three-tiered network model which consist of relay nodes (RNs), application nodes (ANs) and sensor nodes (SNs). Under this architecture, the goal of lower-tier SNs is to sense the playing fields and middle-tier ANs only need to gather data from their clusters; Upper-tier RNs are designed to route information as efficiently as possible. In this paper, we first formulate the three-tiered WSN's model as well as the power consumption model of WSNs. Then considering one dimension relaying, we figure out the RNs' optimal placement for each AN which can considerably minimize the total power consumption for WSNs. Finally, we give some criteria for two-dimension relaying.

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-ary phase shift keying (M-PSK) with maximum ratio combining (MRC) in generalized Rician fading channels. Using decision variable (DV)-based and signal-to-noise ratio (SNR)-based moment generating function (MGF) approaches, error and outage probability formulas, and SNR statistics for the M-PSK MRC receiver are derived, taking into account the effects of ICE and all relevant system and channel parameters. We analytically quantify the average SNR (ASNR) loss of M-PSK caused by ICE, and provided a unified MGF expression for ICE and different M's. In addition, we point out a major approximation for a popular approach used in the literature to evaluate the adverse effect of Gaussian weighting errors.

A single-carrier quasi-orthogonal distributed block space-time coding scheme for a wireless collaborative network with one relaying stage composed of four nodes is proposed. This block quasi-orthogonal design can attain full diversity and maximum rate, and is based on simple amplify-and-forward processing at the relay nodes. A cyclic prefix is introduced into the block transmission to overcome channel delay mismatches in the paths through the four relays. In single-carrier operation, these delays are shown to introduce inter-symbol-interference (ISI) in the destination signal. A linear pre-processing scheme is therefore designed to mitigate this ISI through maximizing signal-to-interference-plus-noise ratio (SINR) at the receiver in combination with iterative equalization. To reduce the computational complexity of this scheme the underlying interference matrices are rendered sparse by the pre-processing operation. Simulation studies confirm the improvement in SINR of the proposed approach as compared to one which only uses rectangular pre-windowing.

The area of wireless sensor networks (WSNs) has gained significant attention from researchers due to its expansive range of applications, such as industrial regulation, human detection, and medical diagnosis. WSN is a vast number of geographically scattered devices that use sensor nodes to communicate and gather information from the target region. In clustered WSNs, the cluster head (CH) is deliberated as the relay node at a higher energy level than the non-CH nodes. The relay nodes perform more tasks related to the non-CHs, and these relay nodes are restricted by energy and communication capacity. Therefore, balancing the load of the relay node is a significant concern for improving the performance of the WSNs. Clustering is a well-known technique enforced to balance the load of the relay nodes. Often, densely loaded relay nodes dissolve their energy in less time and may cause changes in the topology of the network. In this study, we propose a Quasi-oppositional based Jaya load balancing strategy (QOJ-LBS) with a novel fitness function to address the issue of load balancing. The novel fitness function derived from the convex combination of the least lifespan of the relay node across the network and the entropy value of the lifespan of all relay nodes. The proposed QOJ-LBS justifies the network performance under two different WSN conditions called scenario-1 and scenario-2 with single-hop and multi-hop routing. The experimental analysis shows that improvement in network lifespan, total energy utilization, and the number of active sensor nodes of WSN is statistically significant in proposed QOJ-LBS compared to other state-of-the-art algorithms.

Multimedia delivery over Wireless Sensor Networks (WSNs) is energy critical. In this paper, we study an energy constrained cross layer optimization scheme to improve digital image quality in cross polarization discrimination (XPD) based Multiple Input Multiple Output (MIMO) WSNs. The contribution of this research can be summarized in three parts. First, link layer energy consumption and packet loss ratio in multirate XPD based MIMO WSN are modeled. Secondly, XPD based modulation optimization cross link and physical layer is proposed, achieving considerable energy efficiency. Finally, a new Position-Value (P- V) based Unequal Error Protection (UEP) scheme is studied and discussed in XPD MIMO WSNs, with more efficient resource allocation compared to traditional approaches. Simulation results show the proposed modulation optimization scheme improves energy efficiency considerably, and position based UEP achieves significant distortion-energy gain compared with traditional layer based resource allocation schemes in XPD MIMO WSNs.

CRSN (Cognitive Radio Sensor Networks) have recently gained huge interest as an area of research. Naturally, due to energy limitations in WSN (Wireless Sensor Networks), grouping sensor nodes into clusters has been widely adopted by the research community to overcome the issue of limited energy budget and generally achieve high energy efficiency as well as prolonging network lifetime in large-scale WSN environments. Combining clustering of WSN with MIMO (Multiple Input Multiple Output) is a promising technique used in literature of this research area leading to what is called cooperative MIMO clustered WSN. Compared with existing work, our contributions are: i) Extension of CR (Cognitive Radio) technique to cooperative MIMO clustered WSN in a spectrum sharing sense as well as demonstrating that SISO setting isn't always the best setting for transmission even at small distances. The shift to other settings is more favorable to guarantee not disturbing the primary user while transmitting on the same channel; and ii) Proposing a selection criterion for cooperative MIMO CRSN that chooses the minimum energy setting (SISO/SIMO/MISO/MIMO) to guarantee a proper communication for the secondary CR system under some interference constraint to the primary user as well as satisfying a specific BER requirement for CR secondary system.