A low-complexity channel training method for efficient SVD beamforming over MIMO channels

Singular value decomposition (SVD) beamforming is an attractive tool for reducing the energy consumption of data transmissions in wireless sensor networks whose nodes are equipped with multiple antennas. However, this method is often not practical due to two important shortcomings: it requires channel state information at the transmitter and the computation of the SVD of the channel matrix is generally too complex. To deal with these issues, we propose a method for establishing an SVD beamforming link without requiring feedback of actual channel or SVD coefficients to the transmitter. Concretely, our method takes advantage of channel reciprocity and a power iteration algorithm (PIA) for determining the precoding and decoding singular vectors from received preamble sequences. A low-complexity version that performs no iterations is proposed and shown to have a signal-to-noise-ratio (SNR) loss within 1 dB of the bit error rate of SVD beamforming with least squares channel estimates. The low-complexity method significantly outperforms maximum ratio combining diversity and Alamouti coding. We also show that the computational cost of the proposed PIA-based method is less than the one of using the Golub–Reinsch algorithm for obtaining the SVD. The number of computations of the low-complexity version is an order of magnitude smaller than with Golub–Reinsch. This difference grows further with antenna array size

Error performance analysis of cross QAM and space-time labeling diversity for cross QAM.

Doctoral Degrees. University of KwaZulu-Natal, Durban.Abstract available in the PD

Coverage Performance in MIMO-ZFBF Dense HetNets with Multiplexing and LOS/NLOS Path-Loss Attenuation

The performance of multiple-input multiple-output (MIMO) multiplexing heterogenous cellular networks are often analyzed using a single-exponent path-loss model. Thus, the effect of the expected line-of-sight (LOS) propagation in densified settings is unaccounted for, leading to inaccurate performance evaluation and/or inefficient system design. This is due to the complexity of LOS/non-LOS models in the context of MIMO communications. We address this issue by developing an analytical framework based on stochastic geometry to evaluate the coverage performance. We focus on the zero-forcing beamforming where the maximum signal-to-interference ratio is used for cell association. We analytically derive the coverage. We then investigate the cross-stream interference correlation, and develop two approximations of the coverage: Alzer Approximation (A-A) and Gamma Approximation (G-A). The former is often used in the single antenna and single-stream MIMO. We extend A-A to a MIMO multiplexing system and evaluate its utility. We show that the inverse interference is well-fitted by a Gamma random variable, where its parameters are directly related to the system parameters. The accuracy and robustness of G-A is higher than that of A-A. We observe that depending on the multiplexing gain, it is possible to attain the best coverage probability by proper densification

In-band-full-duplex integrated access and backhaul enabled next generation wireless networks

In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G. Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario. However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors. Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds. Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance. Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios