The spatially distributed adaptive array is defined and analyzed. It is applied to both time division multiple access (TDMA) and code division multiple access (CDMA) cellular networks to improve the outage probability at either the base station or mobiles. In a TDMA network, the distributed array consists of three sub-arrays at alternate corners of a hexagonal cell. It is shown analytically that the SINR of combined beamforming of the distributed sub-arrays is greater than or equal to the SIR or independent beamforming of the sub-arrays. Closed form solutions are derived for estimating the BER performance of Rayleigh fading mobile signals received at a distributed adaptive array with combined beamforming of the sub-arrays. The simulated TDMA uplink outage probability of multiple same-cell co-channel users in a fading environment is compared between conventional, spatially distributed arrays with independent beamforming of the sub-arrays and combined beamforming of the sub-arrays. The effect of the antenna element spacing, number of elements and angular spread is also investigated. Spatially distributed arrays are formed in a CDMA network on the downlink with arrays in multi-way soft handoff with the mobiles. The outage probability performance of combined beamforming of the arrays in handoff is compared to independent beamforming of the arrays as well as to conventional sectorized antennas. The range between mobiles and distributed sub-arrays in the case of a spatially distribu-ted array can be larger than between conventional center cell arrays and mobiles. Therefore, the effect of interference on the range increase relative to an omni antenna of adaptive and phased arrays in a multipath environment for both narrowband and wideband spread spectrum systems is investigated. An analytical model for predicting the asymptotic range limitation of phased arrays when the angular spread exceeds the array beamwidth is derived. / Thesis (PhD (Electronic Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted

This master thesis investigates the possibility of locating LTE base stations, known as eNodeBs, using signal measurements collected by routers on trains. Four existing algorithms for transmitter localization are adopted: the centroid, strongest signal, Monte Carlo path loss simulation and power difference of arrival (PDoA) methods. An improved version of Monte Carlo path loss simulation called logloss fitting is proposed. Furthermore, a novel localization method called sector fitting is presented, which operates solely on the cell identity and geographical distribution of the measurements. The methods are evaluated for a set of manually located eNodeBs, and the results are compared to other external systems that can be used to locate eNodeBs. It is found that the novel sector fitting algorithm is able to considerably improve the accuracy of the logloss fitting and PDoA methods, but weighted centroid is overall the most accurate of the considered methods, providing a median error of approximately 1 km. The Google Geolocation API and Mozilla Location Service still provides estimates that are generally closer to the true location than any of the considered methods. However, for a subset of eNodeBs where measurements from all sectors are available, the novel sector fitting algorithm combined with logloss fitting outperforms the external systems. Therefore, a hybrid approach is suggested, where sector fitting combined with logloss fitting or weighted centroid is used to locate eNodeBs that have measurements from all sectors, while Google Geolocation API or Mozilla Location Service is used to locate the remaining eNodeBs. It is concluded that while the localization performance for those eNodeBs that have measurements from all sectors is relatively good, further improvements to the overall results can likely be obtained in future work by considering environmental factors, the angular losses introduced by directional antennas, and the effects of downlink power control.

Deploying unmanned aerial vehicles (UAVs) as aerial base stations (BSs) in order to assist terrestrial connectivity, has drawn significant attention in recent years. UAV-BSs can take over quickly as service providers during natural disasters and many other emergency situations when ground BSs fail in an unanticipated manner. UAV-BSs can also provide cost-effective Internet connection to users who are out of infrastructure. UAV-BSs benefit from their mobility nature that enables them to change their 3D locations if the demand of ground users changes. In order to effectively make use of the mobility of UAV-BSs in a dynamic network and maximize the performance, the 3D location of UAV-BSs should be continuously optimized. However, solving the location optimization problem of UAV-BSs is NP-hard with no optimal solution in polynomial time for which near optimal solutions have to be exploited. Besides the conventional solutions, i.e. heuristic solutions, machine learning (ML), specifically reinforcement learning (RL), has emerged as a promising solution for tackling the positioning problem of UAV-BSs. The common practice for optimizing the 3D location of UAV-BSs using RL algorithms is assuming fixed location of ground users (i.e., UEs) in addition to defining discrete and limited action space for the agent of RL. In this thesis, we focus on improving the location optimization of UAV-BSs in two ways: 1-Taking into account the mobility of users in the design of RL algorithm, 2-Extending the action space of RL to a continuous action space so that the UAV-BS agent can flexibly change its location by any distance (limited by the maximum speed of UAV-BS). Three types of RL algorithms, i.e. Q-learning (QL), deep Q-learning (DQL) and actor-critic deep Q-learning (ACDQL) have been employed in this thesis to step-by-step improve the performance results of a UAV-assisted cellular network. QL is the first type of RL algorithm we use for the autonomous movement of the UAV-BS in the presence of mobile users. As a solution to the limitations of QL, we next propose a DQL-based strategy for the location optimization of the UAV-BS which largely improves the performance results of the network compared to the QL-based model. Third, we propose an ACDQL-based solution for autonomously moving the UAV-BS in a continuous action space wherein the performance results significantly outperforms both QL and DQL strategies.

It is often necessary to operate a number of radio communication channels from a single control room without time-sharing between the various channels. Here it is necessary to operate a number of transmitters and receivers simultaneously from the same base station or mobile unit without interference. The best method to achieve this has been found in the use of filters inserted in the transmission line between the antenna and the transmitter(s) on one hand and the receiver(s) on the other hand. The basic unit employed in the design of microwave filters is usually a cavity resonator of which the most important factors are the Q, insertion loss and resonant frequency. However, a problem which frequently arises with cavity resonators is the accurate determination of these resonant characteristics complicated by the presence of coupling port, materials and various design and geometrical deviations. Such cavities have been investigated in several cases and the results have been generalised, but this investigation has been conducted to examine thoroughly most of the problems being met in present practice. Design and development of some common resonant structures are considered. Emphasis is placed on solutions found to special problems especially regarding complicated boundary conditions. Furthermore, investigation includes methods for optimising resonant parameters such as insertion loss and Q, trading of insertion loss with coupled cavity selectivity, frequency tuning and compensation for frequency variations due to wide ranges of operating temperatures. By comparing Q values obtained in practice with theoretical values, it has been possible to establish an appropriate Q loss budget to as to facilitate accurate prediction of coupled cavity unloaded Q. A satisfactory agreement between theory and practice has been obtained. By application of the results of theoretical analysis and experiment, it is shown that microwave filters can be designed to have a desired insertion loss and off-band attenuation slope. Steps leading to designs of any number of cascaded cavities in a two-port network and, subsequently, multi-port networks are discussed in detail.

This research study focuses on solving the deployment planning problem for UAV-BSs using Multi-Objective Evolutionary Algorithms (MOEAs). The main research objectives encompass gridbased modelling of the target area, investigating evolution parameters, and evaluating algorithm performance in diverse deployment scenarios. Cost, coverage, and interference are considered as objectives along with specific constraints to generate optimal deployment plans. The solution incorporates objective decision support for selecting the best solution among the Pareto front. The research also accounts for parameter initialization and UAV network heterogeneity. Through comprehensive evaluations, the proposed solution demonstrates computational efficiency and the ability to generate satisfactory deployment plans. The study recommends using NonDominated Sorting Genetic Algorithm-II (NSGA-II) for optimal performance. The research also incorporates a fitness approximation technique to reduce computational time while maintaining solution quality. The findings provide valuable insights and recommendations for efficient and balanced deployment planning. However, the research acknowledges limitations and suggests future enhancements. Overall, this research contributes to the field by establishing a foundation for robust and practical deployment plans, guiding future advancements. Future research should focus on addressing identified limitations to enhance applicability and effectiveness in real-world deployment scenarios.

Yes / RF power amplifiers in mobile WiMAX transceivers operate in an inherently nonlinear manner. It is possible to amplify the signal in the linear region, and avoid distortion, using output power back-off; however, this approach may suffer significant reduction in efficiency and power output. This paper investigates the use of Doherty techniques instead of back-off, to simultaneously achieve good efficiency and acceptable linearity. A 3.5 GHz Doherty RFPA has been designed and optimized using a large signal model simulation of the active device, and performance analysis under different drive levels. However, the Doherty EVM is generally poor for mobile WiMAX. Linearity may be improved by further digital pre-distortion, and a simple pre-distortion method using forward and reverse AM-AM and AM-PM modeling. Measurements on the realized amplifier show that this approach satisfies the EVM requirements for WiMAX base stations. It exhibits a PAE over 60%, and increases the maximum linear output power to 43 dBm, whilst improving the EVM.

Yes / Much attention has been paid to making 5G developments more en-ergy efficient, especially in view of the need for using high data rates with more complex modulation schemes within a limited bandwidth. The concept of the Doherty power amplifier for improving amplifier efficiency is explained in addi-tion to a case study of a 70W asymmetrical Doherty power Amplifier using two GaN HEMTs transistors with peak power ratings of 45W and 25W. The rationale for this choice of power ratio is discussed. The designed circuit works in the 3.4GHz frequency band with 200 MHz bandwidth. Rogers RO4350B substrate with dielectric constant εr=4.66 and thickness 0.035 mm is used. The perfor-mance analysis of the Doherty power amplifier is simulated using AWR MWO software. The simulated results showed that 54-64% drain efficiency has been achieved at 8 dB back-off within the specified bandwidth with an average gain of 10.7 dB.

Future cellular networks are expected to support extremely high data rates and user capacities. This thesis investigates the downlink of a wireless cellular system that takes advantage of multiple antennas at base stations and mobile stations, frequency reuse across all cells, and cooperation among base stations. We identify asynchronous interference resulting from multi-cell communication as a key challenge, prove the existence of a downlink/uplink duality in that case, and present a linear precoding scheme that exploits this duality. Since this result is not directly extendable to orthogonal frequency division multiplexing (OFDM), we propose a `hybrid' algorithm for two cooperating base stations, which combines linear and nonlinear precoding. This algorithm minimizes the sum mean squared error of the system and is extendable to OFDM. Finally, we consider the problem of user selection for multiuser precoding in OFDM-based systems. We extend an available single-cell user selection scheme to multiple cooperating cells.

Future cellular networks are expected to support extremely high data rates and user capacities. This thesis investigates the downlink of a wireless cellular system that takes advantage of multiple antennas at base stations and mobile stations, frequency reuse across all cells, and cooperation among base stations. We identify asynchronous interference resulting from multi-cell communication as a key challenge, prove the existence of a downlink/uplink duality in that case, and present a linear precoding scheme that exploits this duality. Since this result is not directly extendable to orthogonal frequency division multiplexing (OFDM), we propose a `hybrid' algorithm for two cooperating base stations, which combines linear and nonlinear precoding. This algorithm minimizes the sum mean squared error of the system and is extendable to OFDM. Finally, we consider the problem of user selection for multiuser precoding in OFDM-based systems. We extend an available single-cell user selection scheme to multiple cooperating cells.

No / Over the past decade, wireless communications has experienced tremendous growth, and this growth is likely to multiply in the near future. The proliferation of mobile users and an ever increasing demand for multimedia services has resulted in greater capacity requirements. Radio frequency spectrum is scarce and cannot meet this ever increasing demand and the required Quality of Service (QoS) will no longer be achieved if efficient Radio Resource Management (RRM) solutions are not found. Conventional Radio Access Networks (RAN) have standalone Base Stations (BS) with capacity preconfigured for peak loads. These RANs have high call blocking and dropping rates since BSs resources cannot be shared. Cloud based RANs (C-RAN) have been proposed as a cost and energy efficient way of meeting high capacity demand of future wireless access networks by consolidating BSs to the cloud. Instead of relying on rejection of new call requests due to limited BS resources, C-RAN takes benefit of the cloud elasticity, which allows dynamic provisioning of cloud BS resources. This paper presents a novel C-RAN Call Admission Control (C-RAN CAC) to ensure Grade of Service (GoS) by improving blocking probability and improvement of call waiting times. Call blocking probability, call average waiting time and system utilization are used to evaluate the performance of the proposed CAC algorithm.