Fereidoun H. Panahi

In this thesis, a wireless-powered communication network model is considered, in which a multi-antenna access point with limited energy, powered by a dedicated wireless power source, communicates with a mobile user. The dynamics of the mobile user, equipped with a single antenna, are modeled using a well-known random mobility model. To leverage the benefits of using a multi-antenna connection, two well-known schemes for multi-antenna transmission are employed: maximum rate transmission and transmit antenna selection. Unlike previous works that only considered static scenarios, the aim of this thesis is to investigate wireless power and information transmission in a scenario with a randomly moving user under the Nakagami fading scheme. Notably, a specific case of the analysis, i.e., the Rayleigh scheme, has not been empirically well-tested, which further enhances the value of the analysis. By considering the two schemes of maximum rate transmission and transmit antenna selection, closed-form expressions are derived for outage probability, average throughput with delay constraint, average throughput without delay constraint, average bit error rate (BER), and throughput with BER constraint. Thus, the impact of dynamic propagation environments with path loss factors and multi-path parameters on the wireless power source-to-access point and access point-to-mobile user links in the wireless-powered communication network can be evaluated. Finally, by introducing an innovation based on fluid antenna systems, as well as through analytical results and computer simulations, the accuracy of the analyses is validated, and the effects of various parameters on system performance are examined.

Due to the increasing interest in aerial communications, the Third Generation Partnership Project (3GPP), a standardization organization, has considered UAVs supported by LTE as a research priority. Recent research has shown that some popular data files are frequently requested by user equipment (UEs) in wireless communication networks, which account for a significant portion of the data traffic. To reduce transfers and redundant transmissions of files in the network, wireless storage for pre-downloading popular files on devices and the adoption of caching mechanisms have been proposed. In this thesis, potential storage for highly compact small-cell networks with both ground and aerial users has been studied, where a dynamic on-off architecture under a complex loss model is adopted, encompassing both line-of-sight and non-line-of-sight transmissions. Generally, we focus on the successful download probability (SDP) from small-cell base stations (SBS) to UEs, which store requested files under different caching policies. To be more precise, we consider two scenarios. In the first scenario, the SDP is analyzed using stochastic geometry theory, considering the dual-layered UE and SBS distributions as homogeneous Poisson processes. Then, performance constraints on the average SDP for popular caching schemes (PCS) and uniform caching schemes (UCS) are developed. Finally, the impact of key factors such as SBS density, cache size, Zipf distribution exponent, and aerial user height on the average SDP is examined. In the second scenario, the successful download probability is investigated for a more realistic model.

Assisting cellular networks through unmanned aerial vehicles (UAVs) marks a significant advancement in tackling the escalating, diverse, and dynamic traffic demands. The integration of UAVs in wireless communication offers crucial benefits, including precise positioning and favorable line-of-sight (LOS) characteristics. This study explores the deployment of a UAV as an aerial base station (ABS) to support a terrestrial base station (TBS), catering to multiple users in a hotspot area through user offloading. Given the lack of information about user locations, the ABS is presumed to hover at the cell center (geometric center) above the TBS, serving as a best-effort location for all users. Considering the inherent interference between aerial and terrestrial communication links due to spectrum reuse, we investigate the influence of ABS altitude, transmit power, and offload proportion on the users' downlink sum-rate in a LOS channel scenario. Through simulations, we will observe that UAVs can serve as beneficial flying base stations for offloading TBSs in hotspots. However, due to their limited onboard battery capacity, UAVs typically have limited operational durations. Subsequently, the UAV needs to return to a designated charging station for battery replenishment or replacement. This thesis delves deeper into evaluating the performance of the UAV-enabled offloading system, considering factors such as UAV availability, charging station density, and the time required for battery recharging or replacement.

Unmanned aerial vehicles (UAVs), commonly known as drones, can serve as aerial base stations (BSs) to complement macro-BSs in hotspot areas. However, due to the limited battery capacity of drones, they typically operate for less than 1.5 hours before needing to return to a dedicated charging station for battery recharge or replacement. In this thesis, we investigate the performance of a cellular network equipped with drones, while considering the spatial distribution of charging stations. Specifically, we employ tools from stochastic geometry to extract the network coverage probability of the drone-equipped cellular network as a function of battery size, charging station density, and the time required for recharging/replacement. The results indicate that reducing the recharging/replacement time significantly enhances the coverage probability, availability probability, and conditional full-coverage probability, as drones spend less time non-operational and return to servicing the network sooner. Furthermore, increasing the battery capacity of drones results in increased coverage and availability probabilities, as drones with larger battery capacity can remain operational for longer durations before returning to charging stations. Also, increasing the density of charging stations, similar to previous scenarios, leads to an increase in coverage and availability probabilities, as drones do not need to travel long distances to reach charging stations and can recharge themselves immediately, providing services to users. Additionally, choosing the optimal flight speed of drones can significantly reduce energy consumption, achieving a balance between efficient coverage and energy savings for longer flight operations. The simulation results indicate that choosing the appropriate altitude for the drone, the timing of drone landing and takeoff, and the waiting time of the drone in the charging queue will have a significant impact.

Device-to-device (D2D) communication allows nearby devices to connect directly instead of through a base station. Studies often assume devices connect to their closest node. However, realistically the nearest node may not be possible due to wireless conditions, scarcity of energy or if a user does not want a D2D connection. This thesis aims to evaluate the impact of connecting to the nearest available users when a connection to the first nearest user is not possible. To compensate for the scarcity of energy and to enhance spectrum utility, the networks are powered and bolstered by both cognitive radio and energy harvesting from ambient interference. We also propose a distributed mechanism which enables D2D devices to select between the millimeter wave (mmW) band and the microwave band for data transmission depending on the availability of line-of-sight (LOS) and non-LOS (NLOS) links. We have used tools from stochastic geometry to evaluate the performance of the proposed mechanism in terms of the signal-to-interference-plus-noise ratio (SINR) coverage probability.

هنگامی که زیرساخت های ارتباطی به دلیل بلایای طبیعی آسیب می بیند، استفاده از هواپیمای بدون سرنشین (UAV) به عنوان ایستگاه پایه هوایی (BS) و ارتباطات دستگاه به دستگاه از جمله استراتژی های ضروری برای خدمات یکپارچه و قابل اعتماد است. در این پایان نامه، استقرار یک وسیله نقلیه هوایی بدون سرنشین (پهپاد) به عنوان یک ایستگاه پایه هوایی برای ارائه ارتباطات بی سیم به یک منطقه معین مورد تجزیه وتحلیل قرار می گیرد. به طور خاص، همزیستی بین پهپاد، در حالت فروسو و فراسو و یک شبکه ارتباطی دستگاه به دستگاه (D2D)در نظر گرفته شده است. برای این مدل، یک چارچوب تحلیلی برای تحلیل پوشش و نرخ و انرژی مؤثر به دست آمده است. در این سناریو که مکان پهباد ثابت است، میانگین احتمال پوشش و مجموع نرخ سیستم برای کاربران در منطقه به عنوان تابعی از ارتفاع پهپاد و تعداد کاربران D2D ، احتمال انتقال موفقیت آمیز (در حالت فراسو) و میانگین مجموع نرخ و EE شبکه بر اساس اصول هندسه تصادفی به دست آمده است. نتایج شبیه سازی و تحلیلی نشان می دهد که بسته به تراکم کاربران D2D ، مقادیر بهینه برای ارتفاع پهپاد وجود دارد که منجر به حداکثر مجموع نرخ سیستم و احتمال پوشش می شود. بااین حال، قابلیت اطمینان ارتباطی BS هوایی و بازده انرژی ارتباطات D2D ممکن است به دلیل همزیستی طیف مشترک جفت های D2D و پهبادکاهش یابد. ما همچنین به اثرات تراکم کاربران متصل به UAV و کاربران D2D ، بر روی EE و مجموع نرخ به عنوان معیارهای عملکرد در سناریوی فراسو می پردازیم. در انتها یک راه حل پیشنهادی برای سناریو ایمنی عمومی که در آن برای ارسال یک داده ثابت به تمام کاربران، اعم از کاربران سلولی و کاربران D2D ،پیشنهاد داده ایم که در آن کاربران سلولی قابلیت ارسال داده به D2Dها رادارند.