Habib Mohammed Hussein

This paper investigates the multi-IRS-assisted multi-user millimeter-wave (mm-Wave) communication, in which multiple intelligent reflecting surfaces (IRSs) are deployed in a distributed fashion to support multi-stream transmission from the base station (BS) to users. In particular, we focus on two different IRS deployment scenarios for downlink transmissions: one employing passive IRSs without signal amplification, and the other using active IRSs with added signal amplification. In the passive IRS scenario, we study the joint design of the active beamformer and unit-modulus phase shifters to maximize the user weighting and sum rate performance. In the other case, we evaluate the joint design of amplitude and phase shifters within a multi-active IRS-enabled framework to enhance the sum rate, while considering IRS amplitude control under the constraints of limited power availability and low hardware cost. For both scenarios, we introduce suitable auxiliary variables to derive closed-form expressions, and propose a computationally efficient iterative algorithm to solve the coupled beamforming and reflection design problem. To address the non-convexity in the passive IRS setup, a block coordinate descent (BCD) method is employed based on the fractional programming (FP) technique. For the active IRS configuration, the transmit beamforming is optimized using the weighted minimum mean square error (WMMSE) approach, while successive convex approximation (SCA) is utilized to optimize phase shifts and amplitude coefficients. Numerical results show that the proposed algorithms converge rapidly and achieve significant transmission rate improvements over benchmark schemes while maintaining low computational complexity.

Improved pilot reuse and channel estimation approaches are proposed in this study to mitigate pilot contamination in massive Multiple input multiple Input (MIMO) net works. Pilot contamination is a major issue in circumstances with a high user density, where interference from adjacent users limits system efficiency. We propose a solution to address this by classifying users into active and idle groups based on their resource needs and channel circumstances, hence prioritizing active users for pilot assignment. A weighted graph coloring approach is used to assign pilot symbols to active users, minimizing interference by allocating neighboring users to distinct pilots. Based on their channel gain, each user’s weight indicates their respective signal strength. In order to improve the quality of channel state information and further minimize contamination, we further investigated channel estimation techniques. The findings of the simulation demonstrate that compared to the weighted graph coloring currently in use, the improved pilot contamination mitigation technique offers notable improvements in spectrum efficiency. In dense network environments, these results show how the suggested methodology may enhance the performance of MIMO systems, offering a workable method for system optimization and resource allocation.

Even though Multiple Input Multiple Output (MIMO) systems are one of the greatest innovations in wireless cellular network technology, they still face many challenges as we progress to 6G, hindering their ability to achieve the best throughput. In cellular networks, channel estimations are made using pilot sequences. Deploying these orthogonal time-frequency limited resources leads to pilot contamination, causing incorrect channel estimation due to mixed signals from neighboring cells and vice versa. Previous research has proven that this significantly decreases system performance. To reduce the impact and improve the output of Multiuser MIMO systems, this paper proposes a hybrid model combining Rateless Orthogonal Space-Time Block Codes (ROSTBC), Weighted Graph Coloring Pilot Allocation (WGCPA), and Maximum Likelihood Estimation (MLE). While ROSTBC has the ability to adapt to channel conditions, allowing the system to perform well despite pilot contamination, WGCPA and MLE address the problems of pilot contamination and the accuracy of channel estimation, respectively. The results showed that this hybrid scheme has proven to perform better compared to previously proposed schemes, providing a valuable contribution to reliable Massive MIMO wireless communication.

Different path loss modelsare used to analyze the behavior of terrestrial television signals. The path loss calculated by one model differs from the other depending on different factors they consider. Frequency is one of the main factors included in each model. The frequency variation in the electromagnetic spectrum causes different response for each model. In terrestrial TV signal representation, since it is operating under VHF and UHF spectrum range, the propagation model used to model the signal must be less invariant when the transmitter is operating in VHF and UHF. If the pathloss model used is very variant it is difficult to define the coverage of the transmitters. This causes interference among transmitters and between the digital terrestrial TV transmitters and TV white space devices. Different propagation models are analyzed by their sensitivity to frequency variation from very-high and ultra-high frequency spectrums. After the best model is selected, we have used this model to find the coverage of the incumbent transmitter, which then is used to analyze free channels for secondary use. First the pathloss at VHF and then for UHF is calculated. This difference is then compared and the result indicates that ITU-R P.1546–5, which incorporate terrain data is best of others. Using this model and further analyze the coverage and free channels, we have found a minimum of 408 MHz free contiguous bandwidth, by considering a worst-case scenario, which is placing a WSD at the incumbent transmitter.

The Uniform hexagonal array (UHA) sidelobe level (SLL) reduction is a crucial consideration for avoiding co-channel interference and improving Carrier-to-interference Ratio (CIR) performance in HAP wireless networks using the TVWS spectrum. The SLL reduction in UHA has been researched by applying evolutionary algorithms such as genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, such algorithms have the drawbacks such as early convergence and the inability to reach globally. The beam pointing approaches for UHA antennas using Modified PSO (MPSO), for reducing the SLL on finding the optimal current weights is presented in this article. The UHA antenna array with 19 cells fitted with 169 elements in the HAPs cellular structure is considered to simulate the proposed approach. Then, the MPSO approach is employed and compared with the standard PSO algorithm and Uniform Weighting (UW) scheme. As per the simulation findings, the proposed approach drastically decreased sidelobes, with a reduction of up to -6.84dB and -13.3dB when compared to PSO and UW respectively. In other words, the proposed approach outperforms the UW and the PSO algorithms. Moreover, the CIR performance of the proposed approach has been demonstrated in terms of average outage probability and the proposed approach provides a better result.

The coverage and capacity of exploiting TV White Spaces (TVWS) from High Altitude Platforms (HAPs) with multiple antenna payloads using uniform rectangular phased array (URA) antennas are explored in this article. A scenario is suggested in which a HAP and TVWS base station are installed on the HAP within a HAP coverage area with a radius of 100 km and a cell radius of 10.5 km. A scenario is suggested in which TVWS base stations are installed on a HAP providing coverage to an area of 100 km radius. This area is consisted of a number of cells where each of them has a radius of 10.5 km. The formation of HAP cells with various reuse patterns has been established. An analysis of coverage, capacity and power profile function for TVWS link from 25×25 URA HAP arrays is presented. To minimize the sidelobe levels in the antenna array synthesis, window function has been assumed. Power profile within a cell using URA is highlighted. Channel to Interference (CIR) performance contour, coverage probability and channel capacity have been determined. The channel capacity for the theoretical Shannon bound and practical truncated Shannon bound are determined and compared. Results show that a maximum channel capacity of 53 Mbps can be attained from the proposed model.