Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. However, hybrid structures allow only a lower-dimensional signal to be observed, which adds difficulties for channel covariance matrix estimation. In this paper, we formulate the channel covariance estimation as a structured low-rank matrix sensing problem via Kronecker product expansion and use a low-complexity algorithm to solve this problem. Numerical results with uniform linear arrays (ULA) and uniform squared planar arrays (USPA) are provided to demonstrate the effectiveness of our proposed method

High-dynamic GPS tracking

The results of comparing four different frequency estimation schemes in the presence of high dynamics and low carrier-to-noise ratios are given. The comparison is based on measured data from a hardware demonstration. The tested algorithms include a digital phase-locked loop, a cross-product automatic frequency tracking loop, and extended Kalman filter, and finally, a fast Fourier transformation-aided cross-product frequency tracking loop. The tracking algorithms are compared on their frequency error performance and their ability to maintain lock during severe maneuvers at various carrier-to-noise ratios. The measured results are shown to agree with simulation results carried out and reported previously

Low-Rank Channel Estimation for Millimeter Wave and Terahertz Hybrid MIMO Systems

Massive multiple-input multiple-output (MIMO) is one of the fundamental technologies for 5G and beyond. The increased number of antenna elements at both the transmitter and the receiver translates into a large-dimension channel matrix. In addition, the power requirements for the massive MIMO systems are high, especially when fully digital transceivers are deployed. To address this challenge, hybrid analog-digital transceivers are considered a viable alternative. However, for hybrid systems, the number of observations during each channel use is reduced. The high dimensions of the channel matrix and the reduced number of observations make the channel estimation task challenging. Thus, channel estimation may require increased training overhead and higher computational complexity. The need for high data rates is increasing rapidly, forcing a shift of wireless communication towards higher frequency bands such as millimeter Wave (mmWave) and terahertz (THz). The wireless channel at these bands is comprised of only a few dominant paths. This makes the channel sparse in the angular domain and the resulting channel matrix has a low rank. This thesis aims to provide channel estimation solutions benefiting from the low rankness and sparse nature of the channel. The motivation behind this thesis is to offer a desirable trade-off between training overhead and computational complexity while providing a desirable estimate of the channel

Adaptive multibeam phased array design for a Spacelab experiment

The parametric tradeoff analyses and design for an Adaptive Multibeam Phased Array (AMPA) for a Spacelab experiment are described. This AMPA Experiment System was designed with particular emphasis to maximize channel capacity and minimize implementation and cost impacts for future austere maritime and aeronautical users, operating with a low gain hemispherical coverage antenna element, low effective radiated power, and low antenna gain-to-system noise temperature ratio

THE APPLICATION OF REAL-TIME SOFTWARE IN THE IMPLEMENTATION OF LOW-COST SATELLITE RETURN LINKS

Digital Signal Processors (DSPs) have evolved to a level where it is feasible for digital modems with relatively low data rates to be implemented entirely with software algorithms. With current technology it is still necessary for analogue processing between the RF input and a low frequency IF but, as DSP technology advances, it will become possible to shift the interface between analogue and digital domains ever closer towards the RF input. The software radio concept is a long-term goal which aims to realise software-based digital modems which are completely flexible in terms of operating frequency, bandwidth, modulation format and source coding. The ideal software radio cannot be realised until DSP, Analogue to Digital (A/D) and Digital to Analogue (D/A) technology has advanced sufficiently. Until these advances have been made, it is often necessary to sacrifice optimum performance in order to achieve real-time operation. This Thesis investigates practical real-time algorithms for carrier frequency synchronisation, symbol timing synchronisation, modulation, demodulation and FEC. Included in this work are novel software-based transceivers for continuous-mode transmission, burst-mode transmission, frequency modulation, phase modulation and orthogonal frequency division multiplexing (OFDM). Ideal applications for this work combine the requirement for flexible baseband signal processing and a relatively low data rate. Suitable applications for this work were identified in low-cost satellite return links, and specifically in asymmetric satellite Internet delivery systems. These systems employ a high-speed (>>2Mbps) DVB channel from service provider to customer and a low-cost, low-speed (32-128 kbps) return channel. This Thesis also discusses asymmetric satellite Internet delivery systems, practical considerations for their implementation and the techniques that are required to map TCP/IP traffic to low-cost satellite return links