Mohammad Patwary

Bio: Mohammad Patwary is an academic researcher from University of Wolverhampton. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 14, co-authored 91 publications receiving 723 citations. Previous affiliations of Mohammad Patwary include Lancaster University & University of New South Wales.

Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future

Abstract: The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated artificial intelligence (AI) operations. However, fully intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the sixth generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies, such as large intelligent surfaces, electromagnetic–orbital angular momentum, visible light communications, and cell-free communications, to name a few. Our vision for 6G is a massively connected complex network capable of rapidly responding to the users’ service calls through real-time learning of the network state as described by the network edge (e.g., base-station locations and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of machine learning (ML), quantum computing (QC), and quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state of the art in the domains of ML (including deep learning), QC, and QML and identify their potential benefits, issues, and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network infrastructure, network edge, air interface, and user end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed.

Non-Coherent and Backscatter Communications: Enabling Ultra-Massive Connectivity in 6G Wireless Networks

Abstract: With the commencement of the 5th generation (5G) of wireless networks, researchers around the globe have started paying their attention to the imminent challenges that may emerge in the beyond 5G (B5G) era. Various revolutionary technologies and innovative services are offered in 5G networks, which, along with many principal advantages, are anticipated to bring a boom in the number of connected wireless devices and the types of use-cases that may cause the scarcity of network resources. These challenges partly emerged with the advent of massive machine-type communications (mMTC) services, require extensive research innovations to sustain the evolution towards enhanced-mMTC (e-mMTC) with the scalable network cost in 6th generation (6G) wireless networks. Towards delivering the anticipated massive connectivity requirements with optimal energy and spectral efficiency besides low hardware cost, this paper presents an enabling framework for 6G networks, which utilizes two emerging technologies, namely, non-coherent communications and backscatter communications (BsC). Recognizing the coherence between these technologies for their joint potential of delivering e-mMTC services in the B5G era, a comprehensive review of their state-of-the-art is conducted. The joint scope of non-coherent and BsC with other emerging 6G technologies is also identified, where the reviewed technologies include unmanned aerial vehicles (UAVs)-assisted communications, visible light communications (VLC), quantum-assisted communications, reconfigurable large intelligent surfaces (RLIS), non-orthogonal multiple access (NOMA), and machine learning (ML)-aided intelligent networks. Subsequently, the scope of these enabling technologies for different device types (e.g., UAVs, body implants, etc), service types (e.g., e-mMTC), and optimization parameters (e.g., spectrum, energy, cost) is analyzed. Finally, in the context of the proposed non-coherent and BsCs based framework for e-mMTCs, some promising future research directions and open research challenges are highlighted.

Effect of Directional Antenna on the Doppler Spectrum in 3-D Mobile Radio Propagation Environment

Abstract: In this paper, an analytical model is proposed for a macrocellular communication system with directional antennas at elevated base station (BS) to quantify the effect of directivity of the radiated waves from antennas on the Doppler spectrum in a 3-D radio propagation environment. The impacts of antenna beamwidth and motion of mobile station (MS) are thoroughly investigated on the statistical distribution of the power Doppler spectrum. Closed-form expressions for trivariate probability density functions (pdfs) of propagation path distance, power, and Doppler shift are derived. Furthermore, general expressions for joint and marginal pdfs of elevation angle of arrival, power, and Doppler shift are established. Finally, the obtained theoretical results, along with the observations that illustrate the effect of directivity of the antenna beamwidth and the direction of the MS's motion on the distribution characteristics of the power Doppler spectrum, are presented. It is established that for motion of the MS in all directions, the spread in distribution of the Doppler shift observed is significantly reduced due to the use of a directional antenna at the BS with a narrow beam directed toward the desired user. It is also observed that, for a sharp azimuthal beam of directional antenna, the multipath components corresponding to the scatterers in the elevation plane result in the reduction of Doppler shift with an increase in their vertical distance from the MS.

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Abstract: The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

What should 6G be

Abstract: The standardization of fifth generation (5G) communications has been completed, and the 5G network should be commercially launched in 2020. As a result, the visioning and planning of 6G communications has begun, with an aim to provide communication services for the future demands of the 2030s. Here, we provide a vision for 6G that could serve as a research guide in the post-5G era. We suggest that human-centric mobile communications will still be the most important application of 6G and the 6G network should be human centric. Thus, high security, secrecy and privacy should be key features of 6G and should be given particular attention by the wireless research community. To support this vision, we provide a systematic framework in which potential application scenarios of 6G are anticipated and subdivided. We subsequently define key potential features of 6G and discuss the required communication technologies. We also explore the issues beyond communication technologies that could hamper research and deployment of 6G. This Perspective provides a vision for sixth generation (6G) communications in which human-centric mobile communications are considered the most important application, and high security, secrecy and privacy are its key features.

A Survey of Channel Modeling for UAV Communications

Abstract: Unmanned aerial vehicles (UAVs) have attracted great interest in rapid deployment for both civil and military applications. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. Accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non–stationary channels. Additionally, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey of the measurement methods proposed for UAV channel modeling that use low altitude platforms and discusses various channel characterization efforts. We also review from a contemporary perspective of UAV channel modeling approaches, and outline future research challenges in this domain.