Analysis and optimisation of SWIPT networks.

Energy harvesting (EH), which refers to replenishing energy from the environment, is demonstrated to be a promising approach in reducing the operational expenses (OPEX) and increasing the network lifetime of emerging wireless communication technologies by eliminating the need for frequent battery replacing or recharging of wireless devices. Among various ambient energy sources, the focus of this dissertation is on wireless power transfer (WPT) considering the unique characteristic of radio frequency (RF) signals; that is, they inherently carry both information and energy. A particularly interesting scenario arises when sources support simultaneous wireless information and power transfer (SWIPT) to provide a remote, controllable, and on-demand energy source. In this context, one of the promising deployment approaches is SWIPT-enabled cognitive radio networks (CRNs), which offer significant gains in terms of spectral and energy efficiencies. One of the practical scenarios of RF-powered CRN is deploying a number of distributed cognitive sensor nodes, equipped with RF EH modules, to sense a specific area and send the sensed data to an access point while coexisting with a primary licensed network. However, exploiting the full potentials of SWIPT-enabled CRNs is subject to carefully aligning the requirements of the EH unlicensed secondary receivers (SRs) with those of the legitimate primary receivers (PRs). In light of this, the first contribution of this thesis focuses on investigating the problem of beamforming for the downlink of multi-user multiple-input single-output (MU-MISO) CRNs. With the objective of minimising the transmission power of the secondary base station (SBS), optimal and suboptimal solutions for the formulated optimisation problem are provided by jointly optimising the transmit beamforming vector at the SBS and adjusting the parameters of the energy harvesters at the SRs. It is shown that the obtained solutions are efficient in meeting the EH and quality-of-service (QoS) requirements of the SRs and the levels of interference accepted by the PRs. Apart from SWIPT-enabled CRNs, relay-assisted SWIPT networks are envisioned to be a promising framework offering extended coverage, diversity gains, and enhanced energy efficiency. In this case, the relay network itself can benefit from the relayed transmissions in terms of saving energy, and the harvested energy can be used to charge relay nodes and extend their lifetime as compensation for their role of data forwarding. Nonetheless, a concrete performance analysis on the impact of the involved system parameters such as, the energy conversion efficiency and the location of the EH relay terminal, on the trade-off between the achievable information transfer efficiency and the harvested energy level is crucial for the successful implementation of SWIPT in this context. This inspired the research work in the next two contributions with the main focus on developing novel comprehensive analytical frameworks for the investigation and evaluation of SWIPT relaying systems. Specifically, the second contribution is dedicated to examining the application of noncoherent modulation, which is recognised as an energy efficient modulation scheme for SWIPT, due to its ability to eliminate the need of instantaneous channel state information (CSI) estimation/tracking. Through adopting a moments-based approach, novel expressions are derived for the outage probability, achievable throughput, and average symbol error rate (ASER) of dual-hop SWIPT relaying systems. Furthermore, new asymptotic analytical results are derived for the high SNR regime and are then utilised to analytically quantify the achievable diversity order. The proposed mathematical tools are demonstrated to be an accurate and efficient means by which one can conduct a thorough analysis on the system performance without the burden of Monte Carlo simulations. Finally, the third contribution focuses on SWIPT relaying systems operating in the presence of impulsive non-Gaussian noise, which is typical in several practical scenarios. Several studies show sufficient evidences that impulse man-made noise is encountered in various metropolitan, indoor, and underwater wireless applications. Examples of these sources include automotive ignition, electronic devices, household appliances, medical equipment, and industrial equipment. To characterise the behavior of the system performance under this type of noise, an efficient analytical framework is developed where novel closed-form xpressions for the pairwise error probability (PEP) are derived for two relaying schemes, namely, blind relaying and CSI-assisted relaying, employed under two assumptions imposed on the deployed EH process; namely, instantaneous EH (IEH) and average EH (AEH). Apart from being accurate, the derived expressions are shown to be efficient in quantifying the diversity order of the system and providing a comprehensive study on the impact of the severity of impulsive noise on the behavior of the system.

[1]  Derrick Wing Kwan Ng,et al.  Simultaneous wireless information and power transfer in modern communication systems , 2014, IEEE Communications Magazine.

[2]  Wei Zhong,et al.  AN-Aided Secrecy Precoding for SWIPT in Cognitive MIMO Broadcast Channels , 2015, IEEE Communications Letters.

[3]  Julian Cheng,et al.  Performance of SWIPT-Based Differential AF Relaying Over Nakagami- $m$ Fading Channels With Direct Link , 2018, IEEE Wireless Communications Letters.

[4]  D. Middleton Canonical and Quasi-Canonical Probability Models of Class a Interference , 1983, IEEE Transactions on Electromagnetic Compatibility.

[5]  Nikos D. Sidiropoulos,et al.  Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming , 2009, IEEE Transactions on Signal Processing.

[6]  Mohamed-Slim Alouini,et al.  Half-Duplex and Full-Duplex AF and DF Relaying With Energy-Harvesting in Log-Normal Fading , 2017, IEEE Transactions on Green Communications and Networking.

[7]  Khaled Ben Letaief,et al.  Outage Probability of Energy Harvesting Relay-Aided Cooperative Networks Over Rayleigh Fading Channel , 2014, IEEE Transactions on Vehicular Technology.

[8]  Sungsoo Park,et al.  Spectrum Sensing Optimization for Energy-Harvesting Cognitive Radio Systems , 2014, IEEE Transactions on Wireless Communications.

[9]  Leila Musavian,et al.  Joint Beamforming and User Maximization Techniques for Cognitive Radio Networks Based on Branch and Bound Method , 2010, IEEE Transactions on Wireless Communications.

[10]  N. Shinohara,et al.  Power without wires , 2011, IEEE Microwave Magazine.

[11]  Derrick Wing Kwan Ng,et al.  Robust Beamforming for Secure Communication in Systems With Wireless Information and Power Transfer , 2013, IEEE Transactions on Wireless Communications.

[12]  Inkyu Lee,et al.  Outage Probability Analysis and Power Splitter Designs for SWIPT Relaying Systems With Direct Link , 2017, IEEE Communications Letters.

[13]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[14]  D. Rajan Probability, Random Variables, and Stochastic Processes , 2017 .

[15]  Björn E. Ottersten,et al.  Information and Energy Cooperation in Cognitive Radio Networks , 2014, IEEE Transactions on Signal Processing.

[16]  Muhammad R. A. Khandaker,et al.  Robust Power-Splitting SWIPT Beamforming for Broadcast Channels , 2016, IEEE Communications Letters.

[17]  P. A. Delaney,et al.  Signal detection in multivariate class-A interference , 1995, IEEE Trans. Commun..

[18]  Ali A. Nasir,et al.  Relaying Protocols for Wireless Energy Harvesting and Information Processing , 2012, IEEE Transactions on Wireless Communications.

[19]  Xiang Cheng,et al.  Relay Selection in Two-Way Full-Duplex Energy-Harvesting Relay Networks , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[20]  A. Spaulding,et al.  Optimum Reception in an Impulsive Interference Environment - Part I: Coherent Detection , 1977, IEEE Transactions on Communications.

[21]  Murat Uysal,et al.  Cooperative diversity in the presence of impulsive noise , 2009, IEEE Transactions on Wireless Communications.

[22]  Z. Popovic,et al.  Cut the Cord: Low-Power Far-Field Wireless Powering , 2013, IEEE Microwave Magazine.

[23]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[24]  Caijun Zhong,et al.  Wireless Information and Power Transfer With Full Duplex Relaying , 2014, IEEE Transactions on Communications.

[25]  Phone Lin,et al.  Toward self-sustainable cooperative relays: state of the art and the future , 2015, IEEE Communications Magazine.

[26]  Il-Min Kim,et al.  Noncoherent Relaying in Energy Harvesting Communication Systems , 2015, IEEE Transactions on Wireless Communications.

[27]  Qihui Wu,et al.  Cognitive Internet of Things: A New Paradigm Beyond Connection , 2014, IEEE Internet of Things Journal.

[28]  Wu He,et al.  Internet of Things in Industries: A Survey , 2014, IEEE Transactions on Industrial Informatics.

[29]  Ying-Chang Liang,et al.  Robust Downlink Beamforming in Multiuser MISO Cognitive Radio Networks With Imperfect Channel-State Information , 2010, IEEE Transactions on Vehicular Technology.

[30]  Bruno Clerckx,et al.  Joint Beamforming Design for Multi-User Wireless Information and Power Transfer , 2014, IEEE Transactions on Wireless Communications.

[31]  Bo Hu,et al.  Optimal Transceiver Design for SWIPT in $K$-User MIMO Interference Channels , 2016, IEEE Transactions on Wireless Communications.

[32]  M.C. van Beurden,et al.  Analytical models for low-power rectenna design , 2005, IEEE Antennas and Wireless Propagation Letters.

[33]  Xin Liu,et al.  Collaborative Energy and Information Transfer in Green Wireless Sensor Networks for Smart Cities , 2018, IEEE Transactions on Industrial Informatics.

[34]  Sergio Barbarossa,et al.  Cognitive MIMO radio , 2008, IEEE Signal Processing Magazine.

[35]  Sungsoo Park,et al.  Optimal Spectrum Access for Energy Harvesting Cognitive Radio Networks , 2013, IEEE Transactions on Wireless Communications.

[36]  Wireless Connectivity for the Internet of Things , 2014 .

[37]  Dimitrios Hatzinakos,et al.  Analytic alpha-stable noise modeling in a Poisson field of interferers or scatterers , 1998, IEEE Trans. Signal Process..

[38]  Jun Li,et al.  Simultaneous Wireless Information and Power Transfer (SWIPT): Recent Advances and Future Challenges , 2018, IEEE Communications Surveys & Tutorials.

[39]  Marco Fantuzzi,et al.  Scavenging for Energy: A Rectenna Design for Wireless Energy Harvesting in UHF Mobile Telephony Bands , 2017, IEEE Microwave Magazine.

[40]  Ke Wu,et al.  Towards Low-Power High-Efficiency RF and Microwave Energy Harvesting , 2014, IEEE Transactions on Microwave Theory and Techniques.

[41]  Pingzhi Fan,et al.  Wireless information and power transfer in two-way relaying network with non-coherent differential modulation , 2015, EURASIP J. Wirel. Commun. Netw..

[42]  Sungsoo Park,et al.  Optimal mode selection for cognitive radio sensor networks with RF energy harvesting , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[43]  Adrish Banerjee,et al.  Energy Harvesting Cognitive Radio With Channel-Aware Sensing Strategy , 2014, IEEE Communications Letters.

[44]  Lav R. Varshney,et al.  Transporting information and energy simultaneously , 2008, 2008 IEEE International Symposium on Information Theory.

[45]  Xuan Li,et al.  Joint Beamforming Design and Time Allocation for Wireless Powered Communication Networks , 2014, IEEE Communications Letters.

[46]  Rui Zhang,et al.  Cognitive Wireless Powered Network: Spectrum Sharing Models and Throughput Maximization , 2015, IEEE Transactions on Cognitive Communications and Networking.

[47]  Yiwei Thomas Hou,et al.  Wireless power transfer and applications to sensor networks , 2013, IEEE Wireless Communications.

[48]  Kee Chaing Chua,et al.  Secrecy wireless information and power transfer with MISO beamforming , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[49]  Mohamed-Slim Alouini,et al.  Outage probability of diversity systems over generalized fading channels , 2000, IEEE Trans. Commun..

[50]  Bengt Ahlgren,et al.  Internet of Things for Smart Cities: Interoperability and Open Data , 2016, IEEE Internet Computing.

[51]  Theodore S. Rappaport,et al.  Characteristics of impulsive noise in the 450-MHz band in hospitals and clinics , 1998 .

[52]  Xiaoming Chen,et al.  Wireless Energy and Information Transfer Tradeoff for Limited-Feedback Multiantenna Systems With Energy Beamforming , 2013, IEEE Transactions on Vehicular Technology.

[53]  Victor C. M. Leung,et al.  Green Internet of Things for Smart World , 2015, IEEE Access.

[54]  Mohamed-Slim Alouini,et al.  Performance Analysis of Free-Space Optical Links Over Málaga ($\mathcal{M} $) Turbulence Channels With Pointing Errors , 2018, IEEE Transactions on Wireless Communications.

[55]  Mohammad Reza Soleymani,et al.  A Novel Machine-to-Machine Communication Strategy Using Rateless Coding for the Internet of Things , 2016 .

[56]  Sungsoo Park,et al.  Achievable Throughput of Energy Harvesting Cognitive Radio Networks , 2014, IEEE Transactions on Wireless Communications.

[57]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[58]  Björn E. Ottersten,et al.  Beamforming for MISO Interference Channels with QoS and RF Energy Transfer , 2013, IEEE Transactions on Wireless Communications.

[59]  Zhu Han,et al.  Wireless Networks With RF Energy Harvesting: A Contemporary Survey , 2014, IEEE Communications Surveys & Tutorials.

[60]  Hamid Aghvami,et al.  Cognitive Machine-to-Machine Communications for Internet-of-Things: A Protocol Stack Perspective , 2015, IEEE Internet of Things Journal.

[61]  Il-Min Kim,et al.  Energy Harvesting Noncoherent Cooperative Communications , 2015, IEEE Transactions on Wireless Communications.

[62]  I. M. Pyshik,et al.  Table of integrals, series, and products , 1965 .

[63]  Ahmed Sultan Sensing and Transmit Energy Optimization for an Energy Harvesting Cognitive Radio , 2012, IEEE Wireless Communications Letters.

[64]  K. Mayaram,et al.  Efficient Far-Field Radio Frequency Energy Harvesting for Passively Powered Sensor Networks , 2008, IEEE Journal of Solid-State Circuits.

[65]  David Middleton,et al.  Statistical-Physical Models of Electromagnetic Interference , 1977, IEEE Transactions on Electromagnetic Compatibility.

[66]  Sungsoo Park,et al.  Cognitive Radio Networks with Energy Harvesting , 2013, IEEE Transactions on Wireless Communications.

[67]  A.V. Alejos,et al.  Interference and impairments in radio communication systems due to industrial shot noise , 2007, 2007 IEEE International Symposium on Industrial Electronics.

[68]  Bamidele Adebisi,et al.  Outage probability analysis of WPT systems with multiple-antenna access point , 2016, 2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP).

[69]  Insoo Koo,et al.  Access Strategy for Hybrid Underlay-Overlay Cognitive Radios With Energy Harvesting , 2014, IEEE Sensors Journal.

[70]  Murat Uysal,et al.  Cooperative Diversity with Multiple-Antenna Nodes in Fading Relay Channels , 2008, IEEE Transactions on Wireless Communications.

[71]  Joseph A. Paradiso,et al.  Energy scavenging for mobile and wireless electronics , 2005, IEEE Pervasive Computing.

[72]  Xiangyun Zhou,et al.  Cutting the last wires for mobile communications by microwave power transfer , 2014, IEEE Communications Magazine.

[73]  Rajarathnam Chandramouli,et al.  Dynamic Spectrum Access with QoS and Interference Temperature Constraints , 2007, IEEE Transactions on Mobile Computing.

[74]  Gerhard P. Hancke,et al.  A Survey on 5G Networks for the Internet of Things: Communication Technologies and Challenges , 2018, IEEE Access.

[75]  Mohamed-Slim Alouini,et al.  Digital Communication Over Fading Channels: A Unified Approach to Performance Analysis , 2000 .

[76]  Hsiao-Hwa Chen,et al.  Enhancing wireless information and power transfer by exploiting multi-antenna techniques , 2015, IEEE Communications Magazine.

[77]  Bayan S. Sharif,et al.  Wireless Information and Power Transfer in Cooperative Networks With Spatially Random Relays , 2014, IEEE Transactions on Wireless Communications.

[78]  Geng Wu,et al.  M2M: From mobile to embedded internet , 2011, IEEE Communications Magazine.

[79]  Jun Huang,et al.  Simultaneous Wireless Information and Power Transfer: Technologies, Applications, and Research Challenges , 2017, IEEE Communications Magazine.

[80]  Deqiang Chen,et al.  Cooperative diversity for wireless fading channels without channel state information , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[81]  Theodore S. Rappaport,et al.  Measurements and Models of Radio Frequency Impulsive Noise for Indoor Wireless Communications , 1993, IEEE J. Sel. Areas Commun..

[82]  Hubregt J. Visser,et al.  RF Energy Harvesting and Transport for Wireless Sensor Network Applications: Principles and Requirements , 2013, Proceedings of the IEEE.

[83]  H. Vincent Poor,et al.  Efficient estimation of Class A noise parameters via the EM algorithm , 1991, IEEE Trans. Inf. Theory.

[84]  Mohamed-Slim Alouini,et al.  Energy-harvesting in cooperative AF relaying networks over log-normal fading channels , 2016, 2016 IEEE International Conference on Communications (ICC).

[85]  Anant Sahai,et al.  Shannon meets Tesla: Wireless information and power transfer , 2010, 2010 IEEE International Symposium on Information Theory.

[86]  Naoki Shinohara,et al.  The wireless power transmission: inductive coupling, radio wave, and resonance coupling , 2012 .

[87]  Rui Zhang,et al.  Wireless powered communication: opportunities and challenges , 2014, IEEE Communications Magazine.

[88]  Tsung-Hui Chang,et al.  Joint Beamforming and Power Splitting for MISO Interference Channel With SWIPT: An SOCP Relaxation and Decentralized Algorithm , 2014, IEEE Transactions on Signal Processing.

[89]  Xiao Lu,et al.  Dynamic spectrum access in cognitive radio networks with RF energy harvesting , 2014, IEEE Wireless Communications.

[90]  Hong-Chuan Yang,et al.  Simultaneous Wireless Information and Power Transfer in Cooperative Relay Networks With Rateless Codes , 2015, IEEE Transactions on Vehicular Technology.

[91]  J. Ritcey,et al.  Pade approximations of probability density functions , 1994 .

[92]  Tharmalingam Ratnarajah,et al.  Joint Transceiver Beamforming in MIMO Cognitive Radio Network Via Second-Order Cone Programming , 2012, IEEE Transactions on Signal Processing.

[93]  Leandros Tassiulas,et al.  Convex approximation techniques for joint multiuser downlink beamforming and admission control , 2008, IEEE Transactions on Wireless Communications.

[94]  Liang Liu,et al.  Joint Transmit Beamforming and Receive Power Splitting for MISO SWIPT Systems , 2013, IEEE Transactions on Wireless Communications.

[95]  Murat Uysal,et al.  Impact of receive diversity on the performance of amplify-and-forward relaying under APS and IPS power constraints , 2006, IEEE Communications Letters.

[96]  Liuqing Yang,et al.  Distributed Laser Charging: A Wireless Power Transfer Approach , 2017, IEEE Internet of Things Journal.

[97]  Victor C. M. Leung,et al.  Opportunistic communications in interference alignment networks with wireless power transfer , 2015, IEEE Wireless Communications.

[98]  Mohamed-Slim Alouini,et al.  A unified approach to the probability of error for noncoherent and differentially coherent modulations over generalized fading channels , 1998, IEEE Trans. Commun..

[99]  Robert Schober,et al.  Relay Selection for Simultaneous Information Transmission and Wireless Energy Transfer: A Tradeoff Perspective , 2013, IEEE Journal on Selected Areas in Communications.

[100]  Mubashir Husain Rehmani,et al.  Cognitive-Radio-Based Internet of Things: Applications, Architectures, Spectrum Related Functionalities, and Future Research Directions , 2017, IEEE Wireless Communications.

[101]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[102]  Hongbin Li,et al.  Differential Modulation for Cooperative Wireless Systems , 2007, IEEE Transactions on Signal Processing.

[103]  Liang Yin,et al.  Optimal saving-sensing-transmitting structure in self-powered cognitive radio systems with wireless energy harvesting , 2013, 2013 IEEE International Conference on Communications (ICC).

[104]  Federico Viani,et al.  Array Designs for Long-Distance Wireless Power Transmission: State-of-the-Art and Innovative Solutions , 2013, Proceedings of the IEEE.

[105]  Sami Muhaidat,et al.  Unified Analysis of Diversity Reception in the Presence of Impulsive Noise , 2017, IEEE Transactions on Vehicular Technology.

[106]  Prusayon Nintanavongsa,et al.  Design Optimization and Implementation for RF Energy Harvesting Circuits , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[107]  Derrick Wing Kwan Ng,et al.  Multiobjective Resource Allocation for Secure Communication in Cognitive Radio Networks With Wireless Information and Power Transfer , 2014, IEEE Transactions on Vehicular Technology.

[108]  Kee Chaing Chua,et al.  Wireless Information Transfer with Opportunistic Energy Harvesting , 2012, IEEE Transactions on Wireless Communications.

[109]  J. C. Mankins,et al.  Space solar power programs and microwave wireless power transmission technology , 2002 .

[110]  Rui Zhang,et al.  Wireless powered communication networks: an overview , 2015, IEEE Wireless Communications.

[111]  Kaibin Huang,et al.  Opportunistic Wireless Energy Harvesting in Cognitive Radio Networks , 2013, IEEE Transactions on Wireless Communications.

[112]  Jiaru Lin,et al.  An online energy allocation strategy for energy harvesting cognitive radio systems , 2013, 2013 International Conference on Wireless Communications and Signal Processing.

[113]  Ran Gozali,et al.  Space-Time Codes for High Data Rate Wireless Communications , 2002 .

[114]  Qi Zhang,et al.  Robust Transceiver Design for Wireless Information and Power Transmission in Underlay MIMO Cognitive Radio Networks , 2014, IEEE Communications Letters.

[115]  Gregory D. Durgin,et al.  Harvesting Wireless Power: Survey of Energy-Harvester Conversion Efficiency in Far-Field, Wireless Power Transfer Systems , 2014, IEEE Microwave Magazine.

[116]  Gregory W. Wornell,et al.  Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks , 2003, IEEE Trans. Inf. Theory.

[117]  David Middleton,et al.  Non-Gaussian Noise Models in Signal Processing for Telecommunications: New Methods and Results for Class A and Class B Noise Models , 1999, IEEE Trans. Inf. Theory.

[118]  Rui Zhang,et al.  MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer , 2011, IEEE Transactions on Wireless Communications.

[119]  Monisha Ghosh,et al.  Analysis of the effect of impulse noise on multicarrier and single carrier QAM systems , 1996, IEEE Trans. Commun..

[120]  Mazen O. Hasna,et al.  A performance study of dual-hop transmissions with fixed gain relays , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[121]  Ioannis Krikidis,et al.  Simultaneous Information and Energy Transfer in Large-Scale Networks with/without Relaying , 2013, IEEE Transactions on Communications.

[122]  Abbes Amira,et al.  Empowering Technology Enabled Care Using IoT and Smart Devices: A Review , 2018, IEEE Sensors Journal.

[123]  Shuzhong Zhang,et al.  Strong Duality for the CDT Subproblem: A Necessary and Sufficient Condition , 2008, SIAM J. Optim..

[124]  Quanzhong Li,et al.  Energy efficiency optimisation for SWIPT AF two-way relay networks , 2017 .

[125]  Helmut Bölcskei,et al.  Fading relay channels: performance limits and space-time signal design , 2004, IEEE Journal on Selected Areas in Communications.

[126]  Dong-Ho Cho,et al.  New opportunity in ITS - transportation systems with wireless power transfer technology , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).