Scaling up MIMO: Opportunities and Challenges with Very Large Arrays

This paper surveys recent advances in the area of very large MIMO systems. With very large MIMO, we think of systems that use antenna arrays with an order of magnitude more elements than in systems being built today, say a hundred antennas or more. Very large MIMO entails an unprecedented number of antennas simultaneously serving a much smaller number of terminals. The disparity in number emerges as a desirable operating condition and a practical one as well. The number of terminals that can be simultaneously served is limited, not by the number of antennas, but rather by our inability to acquire channel-state information for an unlimited number of terminals. Larger numbers of terminals can always be accommodated by combining very large MIMO technology with conventional time- and frequency-division multiplexing via OFDM. Very large MIMO arrays is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation. The ultimate vision of very large MIMO systems is that the antenna array would consist of small active antenna units, plugged into an (optical) fieldbus.Comment: Accepted for publication in the IEEE Signal Processing Magazine, October 201

Time Reversal with Post-Equalization for OFDM without CP in Massive MIMO

This paper studies the possibility of eliminating the redundant cyclic prefix (CP) of orthogonal frequency division multiplexing (OFDM) in massive multiple-input multiple-output systems. The absence of CP increases the bandwidth efficiency in expense of intersymbol interference (ISI) and intercarrier interference (ICI). It is known that in massive MIMO, different types of interference fade away as the number of base station (BS) antennas tends to infinity. In this paper, we investigate if the channel distortions in the absence of CP are averaged out in the large antenna regime. To this end, we analytically study the performance of the conventional maximum ratio combining (MRC) and realize that there always remains some residual interference leading to saturation of signal to interference (SIR). This saturation of SIR is quantified through mathematical equations. Moreover, to resolve the saturation problem, we propose a technique based on time-reversal MRC with zero forcing multiuser detection (TR-ZF). Thus, the SIR of our proposed TR-ZF does not saturate and is a linear function of the number of BS antennas. We also show that TR-ZF only needs one OFDM demodulator per user irrespective of the number of BS antennas; reducing the BS signal processing complexity significantly. Finally, we corroborate our claims as well as analytical results through simulations.Comment: 7 pages, 3 figure

Computational polarimetric microwave imaging

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure

Beamforming and time reversal imaging for near-field electromagnetic localisation using planar antenna arrays

University of Technology, Sydney. Faculty of Engineering and Information Technology.The localisation of radiating sources of electromagnetic waves in the near-field of a receiver antenna array are of use in a vast range of applications, such as in microwave imaging, wireless communications, RFID, real time localisation systems and remote sensing etc. Localisation of targets embedded in a background dielectric medium, which is usually the case in Radar, UWB imaging and remote sensing, can be done using the scattered response received at the antennas. In this thesis, we investigate methods for localisation of both near-field radiating as well as scattering sources of electromagnetic waves. For localisation of near-field radiating sources, planar antenna arrays such as concentric circular ring array (CCRA), uniform rectangular array (URA), uniform circular array (UCA) and elliptic array are employed. The thesis employs beamforming and parameter estimation methods for localisation and proposes novel algorithms that are based on standard Capon beamformer (SCB), subspace based superresolution algorithms (MUSIC and ESPRIT) and maximum likelihood (ML) methods. Complex array geometries can suffer from severe mutual coupling and are susceptible to array modelling errors. These errors impair the performance of algorithms that are used for beamforming and parameter estimation for localisation. To overcome the limitations of standard Capon beamformer (SCB), a modified capon beamforming method is proposed to make SCB robust against both array modelling error and mutual coupling effects. The proposed method is applied with planar antenna arrays for localisation of near-field sources. Planar arrays are also used with MUSIC and ESPRIT superreso lution algorithms for performance investigation in a near-field source localisation. Here, to reduce the computational burden of standard MUSIC and ESPRIT algorithms, a novel method to estimate the range using the time-delay is proposed. Lastly, to overcome the performance limitations of superresolution algorithms with planar arrays, the ML estimation is investigated for the localisation of near-field sources using planar arrays. Since ML method cannot automatically detect the number of sources, a novel method is proposed here for detecting the number of sources. Finally, performance comparisons of all the methods under investigation have been presented using computer simulations. In order to localise targets embedded either in homogeneous or in heterogeneous background medium, we employ time reversal (TR) techniques that localise based on the received scattering responses from the embedded targets. We propose a novel beamspace- TR technique that can achieve efficient focusing on targets embedded in both a homogeneous and heterogeneous dielectric background media. It is shown that prior to back propagation, applying beamspace processing to the TR operation in the receiving mode helps achieve a reduced dimensional computation and achieves selective focusing. We have also proposed beamspace-TR-MUSIC algorithm for improving the resolution of standard TR-MUSIC algorithm. Performance of these techniques is investigated for localising the target embedded in a clutter rich dielectric background where the dielectric contrast between the target and the background medium is very low. We also propose to extend the maximum likelihood based TR (TR-ML) to improve the focusing ability and to help to localise dielectric targets embedded in a highly cluttered dielectric medium. To prove the ability of the proposed algorithms, they are applied to the problem of UWB radar imaging for the detection of early stage breast cancer. Computer simulations are used for the investigation of the imaging performance of TR, beamspace-TR, TR-MUSIC, beamspace-TR-MUSIC and TR-ML methods on a two-dimensional electromagnetic heterogeneous dielectric scattering model of the breast