Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions

Future wireless systems are envisioned to create an endogenously holography-capable, intelligent, and programmable radio propagation environment, that will offer unprecedented capabilities for high spectral and energy efficiency, low latency, and massive connectivity. A potential and promising technology for supporting the expected extreme requirements of the sixth-generation (6G) communication systems is the concept of the holographic multiple-input multiple-output (HMIMO), which will actualize holographic radios with reasonable power consumption and fabrication cost. The HMIMO is facilitated by ultra-thin, extremely large, and nearly continuous surfaces that incorporate reconfigurable and sub-wavelength-spaced antennas and/or metamaterials. Such surfaces comprising dense electromagnetic (EM) excited elements are capable of recording and manipulating impinging fields with utmost flexibility and precision, as well as with reduced cost and power consumption, thereby shaping arbitrary-intended EM waves with high energy efficiency. The powerful EM processing capability of HMIMO opens up the possibility of wireless communications of holographic imaging level, paving the way for signal processing techniques realized in the EM-domain, possibly in conjunction with their digital-domain counterparts. However, in spite of the significant potential, the studies on HMIMO communications are still at an initial stage, its fundamental limits remain to be unveiled, and a certain number of critical technical challenges need to be addressed. In this survey, we present a comprehensive overview of the latest advances in the HMIMO communications paradigm, with a special focus on their physical aspects, their theoretical foundations, as well as the enabling technologies for HMIMO systems. We also compare the HMIMO with existing multi-antenna technologies, especially the massive MIMO, present various...Comment: double column, 58 page

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Adaptive MIMO Radar for Target Detection, Estimation, and Tracking

We develop and analyze signal processing algorithms to detect, estimate, and track targets using multiple-input multiple-output: MIMO) radar systems. MIMO radar systems have attracted much attention in the recent past due to the additional degrees of freedom they offer. They are commonly used in two different antenna configurations: widely-separated: distributed) and colocated. Distributed MIMO radar exploits spatial diversity by utilizing multiple uncorrelated looks at the target. Colocated MIMO radar systems offer performance improvement by exploiting waveform diversity. Each antenna has the freedom to transmit a waveform that is different from the waveforms of the other transmitters. First, we propose a radar system that combines the advantages of distributed MIMO radar and fully polarimetric radar. We develop the signal model for this system and analyze the performance of the optimal Neyman-Pearson detector by obtaining approximate expressions for the probabilities of detection and false alarm. Using these expressions, we adaptively design the transmit waveform polarizations that optimize the target detection performance. Conventional radar design approaches do not consider the goal of the target itself, which always tries to reduce its detectability. We propose to incorporate this knowledge about the goal of the target while solving the polarimetric MIMO radar design problem by formulating it as a game between the target and the radar design engineer. Unlike conventional methods, this game-theoretic design does not require target parameter estimation from large amounts of training data. Our approach is generic and can be applied to other radar design problems also. Next, we propose a distributed MIMO radar system that employs monopulse processing, and develop an algorithm for tracking a moving target using this system. We electronically generate two beams at each receiver and use them for computing the local estimates. Later, we efficiently combine the information present in these local estimates, using the instantaneous signal energies at each receiver to keep track of the target. Finally, we develop multiple-target estimation algorithms for both distributed and colocated MIMO radar by exploiting the inherent sparsity on the delay-Doppler plane. We propose a new performance metric that naturally fits into this multiple target scenario and develop an adaptive optimal energy allocation mechanism. We employ compressive sensing to perform accurate estimation from far fewer samples than the Nyquist rate. For colocated MIMO radar, we transmit frequency-hopping codes to exploit the frequency diversity. We derive an analytical expression for the block coherence measure of the dictionary matrix and design an optimal code matrix using this expression. Additionally, we also transmit ultra wideband noise waveforms that improve the system resolution and provide a low probability of intercept: LPI)

Application of passive seismic interferometry for local and shallow imaging

Exploratory imaging of the shallow crust is motivated by – (i) the presence of exploitable natural resources, (ii) its influence on seismicity and associated hazards, and (iii) the insights it can provide into the evolution of geological landforms. Keeping in mind these motivations, I use passive seismic interferometry to image the shallow crustal structures. Conventional exploration seismology focuses on local scale imaging using active-source methods (e.g., dynamite, air guns, vibro-seis). In contrast, passive seismic interferometry offers the possibility to use universally available noise sources (both natural and anthropogenic) for subsurface imaging. This approach does not require a spatially and temporally confined seismic source and is thus a cost-effective alternative in logistically challenging environments (e.g., polar ice sheets, exo-planets, etc.). Further, the use of ambient noise as a seismic source minimizes the adverse environmental impact of explosive source experiments in sensitive ecological zones. Ambient noise methods generally utilize low-frequency diffuse noise fields (e.g., microseisms) for global scale imaging of deep earth structures. Application of these methods at shallow scales is challenged by the scarcity of high-frequency ambient noise sources in local settings. Areas away from anthropological activity have very weak noise sources of sufficiently high frequencies. Although, in urban environments some high-frequency sources are available (e.g., traffic, industrial noise), but these are usually confined to a narrow azimuth. Moreover, local noise sources predominantly produce surface waves which have limited vertical and horizontal resolution to be able to image the shallow subsurface. In this dissertation, I focus on the applications of passive seismic interferometry for high-resolution imaging of the shallow subsurface (<1 km depth) by attempting to overcome the challenges and limitations mentioned above. Three diverse application scenarios are presented to demonstrate the versatility of the interferometric methods. These include – (i) Passive P- and S-wave reflectivity imaging in an oil field (Wellington, Kansas) setting using reservoir monitoring data; (ii) Passive seismic imaging of a buried alpine valley (Unaweep, Colorado) to test the hypothesis of Paleozoic glaciation; (iii) Passive seismic imaging for seismic hazard assessment in an urban environment (Enid, Oklahoma). Reflectivity imaging using passive seismic interferometry is generally challenged by the dominance of surface-waves in ambient noise recordings. To overcome this limitation, I develop and implement single-station polarization filters to automatically extract body waves (P- and S-waves) from continuous ambient noise. The extracted waves are then subjected to interferometric processing to retrieve subsurface reflections. This methodology is suitable for sparse and irregular seismic networks such as the previously mentioned reservoir monitoring array. In another application, similar results are achieved by using a teleseismic catalog to extract the P-wave coda. Road-side deployments in the alpine valley and the urban environment mentioned above make linear array geometry feasible. I take advantage of the linear geometry to interferometrically retrieve surface waves propagating along the array which are then inverted to obtain a shear-velocity profile. I compliment the shear-velocity models with results from other passive seismic methods – e.g., structural reflectivity from teleseismic coda-wave autocorrelation, or layer thickness from horizontal-to-vertical spectral ratio analysis. The main results presented in this dissertation includes the retrieval of shallow (< 1 km) structural reflections and the estimation of seismic speed ratio (Vp/Vs) at the Wellington Oil field. This is significant since very few studies have reported the retrieval of S-wave reflectivity using passive seismic methods. In the Unaweep canyon, I image the buried valley floor. The undulating sedimentary-basement interface revealed by the passive imaging suggests the glacial genesis of the canyon. In the Enid study, the high lateral resolution near surface model is well correlated with the site amplification data derived from distributed acoustic sensing. In an urban environment, such experiments are relevant for town-planning and can be used to assess the seismic hazard at sub-kilometer scales

Doctor of Philosophy

dissertationMicrowave/millimeter-wave imaging systems have become ubiquitous and have found applications in areas like astronomy, bio-medical diagnostics, remote sensing, and security surveillance. These areas have so far relied on conventional imaging devices (empl

Efficient method of estimating Direction of Arrival (DOA) in communications systems.

Masters Degree. University of KwaZulu- Natal, Durban.In wireless communications systems, estimation of Direction of Arrival (DOA) has been used both for military and commercial purposes. The signal whose DOA is being estimated, could be a signal that has been reflected from a moving or stationary object, or a signal that has been generated from unwanted or illegal transmitter. When combined with estimating time of arrival, it is also possible to pinpoint the location of a target in space. Localization in space can also be achieved by estimating DOA using two receiving nodes with capability of estimating DOA. The beamforming pattern in smart antenna system is adjusted to emphasize the desired signal and to minimize the interference signal. Therefore, DOA estimation algorithms are critical for estimating the Angle of Arrival (AOA) and beamforming in smart antennas. This dissertation investigates the performance, angular accuracy and resolution of the Minimum Variance Distortionless Response (MVDR), Multiple Signal Classification (MUSIC) and our proposed method Advanced Multiple Signal Classification (A-MUSIC) as DOA algorithms on both Non-Uniform Array (NLA) and Uniform Linear Array (ULA). DOA is critical in antenna design for emphasizing the desired signal and minimizing interference. The scarcity of radio spectrum has fuelled the migration of communication networks to higher frequencies. This has resulted into radio propagation challenges due to the adverse environmental elements otherwise unexperienced at lower frequencies. In rainfall-impacted environments, DOA estimation is greatly affected by signal attenuation and scattering at the higher frequencies. Therefore, new DOA algorithms cognisant of these factors need to be developed and the performance of the existing algorithms quantified. This work investigates the performance of the Conventional Minimum Variance Distortion-less Look (MVDL), Subspace DOA Estimation Methods of Multiple Signal Classification (MUSIC) and the developed hybrid DOA algorithm on a weather impacted wireless channel. The performance of the proposed Advanced-MUSIC (A-MUSIC) algorithm is compared to the conventional DOA estimation algorithms of Minimum Variance Distortionless Response (MVDR) and the Multiple Signal Classification (MUSIC) algorithms for both NLA and ULA antenna arrays. The developed simulation results show that A-MUSIC shows superior performance compared to the two other algorithms in terms of Signal Noise Ratio (SNR) and the number of antenna elements. The results show performance degradation in a rainfall impacted communication network with the developed algorithm showing better performance degradation

Role of Reconfigurable Intelligent Surfaces in 6G Radio Localization: Recent Developments, Opportunities, Challenges, and Applications

Reconfigurable intelligent surfaces (RISs) are seen as a key enabler low-cost and energy-efficient technology for 6G radio communication and localization. In this paper, we aim to provide a comprehensive overview of the current research progress on the RIS technology in radio localization for 6G. Particularly, we discuss the RIS-assisted radio localization taxonomy and review the studies of RIS-assisted radio localization for different network scenarios, bands of transmission, deployment environments, as well as near-field operations. Based on this review, we highlight the future research directions, associated technical challenges, real-world applications, and limitations of RIS-assisted radio localization