فرزاد حسین پناهی

Wireless communication for vehicles is an emerging trend in the automotive and drone industries, offering solutions to pressing issues such as traffic congestion and road or air accidents. Within the framework of the Third Generation Partnership Project (GPP3), vehicle communication is classified as vehicle-to-everything (V2X) communication, encompassing vehicle-to-infrastructure (V2I), vehicle-toperson (V2P), and vehicle-to-vehicle (V2V) communication. V2V communication, in particular, presents diverse applications, including collision avoidance, in-car Internet access, and autonomous driving. The primary objective of vehicle wireless communication is to enhance safety, necessitating low latency and high reliability in such communications.To facilitate direct communication, specialized narrowband short-range communication (DSRC) protocols are employed. Nevertheless, these protocols exhibit functional limitations and fall short of delivering optimal outcomes. Furthermore, DSRC faces restrictions in terms of spectrum availability and data transmission, relying on a 5.9 GHz bandwidth for multiple access control (MAC). However, in CSMA mode and on heavily trafficked roads, its effectiveness diminishes. Additionally, the deployment and operation of DSRC infrastructure, such as Roadside Units (RSUs), incur significant expenses.To address these challenges, the utilization of cellular relay in vehicle communication, along with the application of cellular networks such as LTE and 5G, has been proposed. The 3GPP group has defined several crucial scenarios for V2X and V2V communications, encompassing both direct mode and cellular relay mode. In the direct communication mode, vehicles communicate directly with each other. Conversely, in the cellular relay mode, messages are initially transmitted to the cellular terminal (cellular relay) through a remote connection and suBsequently relayed to the destination device via another remote connection. In the following discussion, drones are employed as cellular relays, and the impacts of drone height, car density, and vehicle-to-vehicle communication are explored. Moreover, the influence of increasing the minimum requested rate on the power and bandwidth allocated by the unmanned aerial vehicle (UAV) to the vehicle is examined.

Cellular networks are struggling in recent years to support high data rates and system capability, as well as the growth of smartphone devices and mobile apps that use data. Future growth has made managing traffic for cell operators one of their biggest difficulties. Mobile data discharge is a low-cost way to lighten the burden on cell phone networks. In this thesis, a method to speed up cell traffic with the device using device communication is presented. The system model structure in question is known as the WPDO Network, and it has been described in this thesis along with how it integrates with power transmission technology. To determine the potential for cellular and D2D users, the structure employs the average power transfer of D2D transmitters and the lowest expected power of base stations. These connections choose the most effective time allocation agent to decide the WPDO network's optimum energy efficiency. We will assess the energy efficiency of the WPDO network by looking at resources with non-geometric forms in two-dimensional space, and by creating an algorithm to maximise WPDO network energy efficiency, we will gain knowledge about network architecture at the system level. Data traffic in cellular networks is greatly decreased as the discharge radius grows due to increased network efficiency, which also impacts the radius of the data evacuation regions. Finally, numerical findings are evaluated and simulated using MATLAB software.

The growing need for wireless connection, as well as the advent of the concept of the Internet of Things, necessitate the development of new communication paradigms that will, in turn, enable a multitude of new applications and disruptive technologies. The current contribution investigates the use of the recently introduced intelligent reflecting surface (IRS) concept in unmanned aerial vehicle (UAV) enabled communications with the goal of extending network coverage and improving communication reliability as well as spectral efficiency of Internet of Things (IoT) networks. We begin by obtaining tractable analytic formulas for the feasible symbol error rate (SER), ergodic capacity, and outage probability of the given setup. We then construct stringent upper and lower constraints for the average signal-to-noise ratio (SNR). Our derivations are then compared to the related asymptotic performance, which demonstrates that the asymptotic SNR lies inside the region between the derived bounds, and approaches either bound depending on the number of reflecting elements (REs). The provided findings show that using the IRS is very effective, as they help to improve the attainable SER by five orders of magnitude. We also show that IRSassisted UAV communication systems can have ten times the capacity of traditional UAV communications in terms of attainable ergodic capacity.

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 موثر 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.

Demand for traffic volumes and high speeds in communication networks continues to grow exponentially. On the other hand, the most valuable factor in these networks is the frequency spectrum, which is limited and with this huge volume of demand is being saturated. One of the solutions proposed in this field is the use of device-to-device (D2D) communication. But another issue in this regard is the supply of energy needed to transmit information in communication (D2D). The solution proposed in this regard is energy harvesting (EH). In the basic paper selected, D2D transmitters derive their energy from environmental interference and will use one of the channels dedicated to cellular network users. In this paper, the two basic approaches of different spectrum access RSA (random spectrum access) and PSA (prioritized spectrum access)) for cellular communications are investigated. In the RSA approach, all available channels, including those used in D2D transmitters, will be randomly used for cellular communications. But in the PSA approach, the channel dedicated to D2D transmitters will be used for cellular communication when all other channels are occupied. In this article, The channel has been used as an influential factor to describe the relationship of energy harvesting And according to that, the probability of outage in the receivers has been investigated. But other energy models can be used to examine the use of energy harvesting in D2D communications. The model used for energy in this paper is a simplified model of energy that is independent of the channel and depends on the wavelength, transmitter power and distance between receiver and transmitter. By considering this energy model, we can rewrite the relationships related to outage and other relationships related to the selected base paper and examine the effect of factors on these relationships and also compare these effects with the base article. But the model used to describe the location of users and base stations is PPP or Poisson point process. The location of mobile systems may exhibit some clustering and repulsion behaviors. Therefore, the DPP model is used to describe the location of users and base stations that incorporate these characteristics. Another article has been selected to investigate this issue, but this article does not use cognitive radio to send information. Using the RSA and PSA models available in the first base paper and used in the PPP model, they can be entered into the DPP model, which are a kind of radio cognitive, and the results can be examined through relationships and simulation results.

One of the most important issues in the analysis and design of wireless telecommunication systems is the discussion of energy consumption. In the past, all cellular networks provided their required energy from the electricity grid. Renewable clean as an effective alternative to reduce the use of energy produced by fossil fuels and store excess energy in base stations and ultimately sell excess energy to the grid and reduce energy costs of the two approaches used The first approach of the base station sleep strategy in the telephone network In order to maximize the energy storage in the network, according to the network traffic load and the second approach, the integration of renewable energy with the electricity network has been done simultaneously for a one-day operational cycle. The aim of the mobile operator is to reduce its total energy cost by optimizing the amount of energy obtained from local renewable energy sources in each time period. The power grid, which is increased by the first approach, is also a constrained optimization used to deal with the uncertainty of renewable energy production.

Numerous types of research have been done in recent years on Multi-Input, Multi-Output, and Massive Multi Input Multi Output. In all of these researches, intercell interface, delay, and Spectral Efficiency have been evaluated. Although Massive MIMO standards in 5G spectral efficiency, Energy efficiency, delay, etc., have been improved significantly, intercell interference issues and handover impact the performance and users' services at the edge of the cell intensely. Cell-Free Massive Multi Input Multi Output as an emerging technology to prepare the users increasing demands and expected increased data rate beyond 5G networks has attracted considerable attention. The main idea of this project is that several distributed Access Points on a limited number of users in one time-frequency block are responsible for the service. In this case, each user receives the services from APs that have the minimum power to delete the intercell interface. Considering the high signaling volume to estimate the channel, signal processing, cooperation, and contribution of APs, it originates essentially to evaluate different levels of signal processing implementation. In this thesis, accomplishments have been made to evaluate four different levels of signal processing or user-centric processing, which are in the best performance. In addition, drone UAVs have been reviewed, which has better performance than user-centric scenarios.

One of the most important issues in the analysis and design of wireless communication systems is investigate of its coverage and efficiency. Coverage efficiency means providing maximum communication coverage and establishing quality communication with users, which maximizing it is one of the main goals in designing new and advanced fifth generation communication systems. In this thesis, we intend to provide communication coverage in the urban environment by using UAVs as aerial BS. First, the factors affecting the efficiency of the coverage by UAVs and the challenges and advantages of these systems are examined. In order to improve the interference situation, we equip drone systems with directional antennas and examine the height of UAVs relative to cells with different congestion using symmetric and asymmetric methods, and finally, control the intercellular interference according to the composition of the directional antenna, symmetric and asymmetric height and frequency reuse. Then we examine the problem of maximum coverage with the minimum number of UAVs and provide a mathematical model to examine all the coverage limitations in the urban environment. Then, we introduce an innovative solution algorithm to improve the coverage situation in the urban environment and examine the system functions for different congestion conditions.

The next generation’s sensor nodes will be more intelligent, energy conservative and perpetual lifetime in the set-up of wireless sensor networks (WSNs). These sensors nodes are facing the overwhelming challenge of energy consumption which gradually decreases the lifetime of overall network. Wireless power transfer (WPT) is one of the most emerging technologies of energy harvesting that deploys at the heart of sensor nodes for efficient lifetime solution. A wireless portable charging device (WPCD) is drifting inside the WSN to recharge all the nodes which are questing for the eternal life. In this paper, we aspire to optimize a multi-objective function for charging trail of WPCD, and self-learning algorithm for data routing jointly. We formulated that the objective functions can optimize the fair energy consumption as well as maximize the routing efficiency of WPCD. The fundamental challenge of the problem is, to integrate the novel path for WPCD by applying the Nodal A* algorithm. We proposed a novel method of sensor node’s training for intellectual data transmission by using of clustering and reinforcement learning (SARSA) defined as clustering SARSA (C-SARSA) along with an optimal solution of objective functions. The whole mechanism outperforms in terms of trade off between energy consumption and stability (fair energy consumption among all nodes) of the WSN, moreover, it prolongs the lifetime of the WSN. The simulated results demonstrate that our proposed method did better than compared literature in terms of energy consumption, stability, and lifetime of the WSN.

In recent years, due to the increase in the number of users and telecommunication towers and the need for high transmission rates, energy consumption in telecommunication systems has increased significantly, which in many cases, including economic and environmental issues. It has brought challenges. Therefore, Green Communication, using the technologies provided in the new generations of wireless communications such as device to device (Dezz Device), as an effective step in managing energy consumption. And its efficiency is known to improve. In device-to-device communication, the information-seeking user communicates with a close user instead of being directly connected to and powered by the base station. In this case, the power consumption of the base station is reduced and the system will be more energy efficient. In this dissertation, first, wireless cellular telecommunication systems are reviewed and then several solutions to reduce energy consumption are presented. The main focus of this research is on energy consumption management in wireless telecommunication systems with two types of cellular and device-to-device communication that part of the power required by the base station is provided by renewable energy sources such as solar and wind.

در دهه ی گذشته، شبکه ی حسگر بیسیم زیرآب (UWSN)، به عنوان زمینه ی پرکاربرد IoUT، مورد توجه بسیاری از مراکز دانشگاهی و صنعتی قرار گرفته است. در ارتباطات بیسیم زیرآب بیشتر محدوده ی طیف فرکانس رادیویی با فرکانس به شدت تضعیف میشود. سیگنال نوری نیز به شدت به ویژگی کدربودن آب دریا وابسته بوده و از اثرات پدیده ی پراکندگی رنج میبرد. در این میان، سیگنال صوتی برگرفته از مزیت انتقال داده بروی مسافتهای طولانی، فنآوری کارآمد و پرکاربرد در لایه ی فیزیکی UWSN، است. رویکرد رایج در لایه ی شبکه ی UWSN، مسیریابی برای انتقال داده های حسگری از گره های زیرآبی به چاهک بروی سطح آب میباشد. مصرف انرژی بالا، تنگنای در منبع توان گره، پهنای باند کم در دسترس، تاخیر انتشار کمابیش بالا برگرفته از سرعت انتشار پائین سیگنال صوتی (1500 متر بر ثانیه)، در کنار ویژگی بی ثبات در زمان و مکان فضای زیرآب، طراحی الگوریتم مسیریابی در UWSN، را دشوار و پیچیده مینماید. مسیریابی Anypath، به عنوان نسل اولیه ی پروتکلهای مسیریابی در UWSN، یک راهبرد کارآمد برای بهره وری انرژی و کنترل میانگین تاخیر انتها به انتها میباشد. در این پایاننامه، با بهره گیری از مزیتهای روشهای یادگیری تقویتی در تعامل با محیط پویا و ناهمگن، یک پروتکل مسیریابی مستقل از موقعیت مکانی گره ی زیرآبی مبتنی بر الگوریتم Q-learning، طراحی و پیشنهاد میشود. به طور خاص، با تعریف دو تابع پاداش وابسته به انرژی و اطلاعات عمق، یک هم وزنی در مصرف انرژی گره های زیرآبی ایجاد میشود. نتایج شبیه سازی در نرم افزار متلب نشان میدهد که پروتکل پیشنهادی با ماهیت تحرک گره های حسگر زیرآبی سازگار میباشد. همچنین، در هم سنجی با دو نمونه ی برجسته از پروتکل مسیریابی در زیرآب، زمان عمر شبکه و تاخیر انتها به انتها در UWSN، را توسعه میدهد.

یکی از مسائل مهم در تحلیل و طراحی سیستم های مخابراتی بیسیم، بهره وری انرژی می باشد. منظور از بهره وری انرژی (Energy Efficiency)، تعداد بیت های انتقال داده شده بین فرستنده و گیرنده در هر واحد ژول انرژی میباشد. در سال های اخیر مصرف انرژی در شبکه های بی سیم و به ویژه در شبکه های تلفن همراه، به دلیل افزایش قابل ملاحظه تعداد کاربران افزایش چشمگیر داشته و تعداد دکل های مخابراتی، به شدت بالا رفته است به گونه ای که بهره وری انرژی به دلیل مسائل زیست محیطی و اقتصادی بعنوان یکی از اهداف عمده طراحی در شبکه های تلفن همراه بی سیم توجه تمام اپراتورهای شبکه و مراکز تحقیقاتی دانشگاهی وصنعتی را به خود جلب کرده است. افزایش تعداد ایستگاه های پایه موجب افزایش مصرف انرژی و افزایش انتشار دی اکسیدکربن گردیده است. در این مقاله ما به بررسی برخی روش های کاهش مصرف انرژی در برنامه مخابرات سبز پرداخته و بر روی روش های زوم سلولی و خواب سلولی که در کاهش مصرف انرژی در شبکه های سلولی مورد استفاده قرار می گیرد تمرکز می نمائیم به گونه ایی که استفاده از روش های مذکور موجب افزایش بهره وری انرژی شود و همچنین الزامات ارائه سرویس به کاربران نیز مد نظر قرار گیرد.

High energy efficiency is an essential item for enabling massive machine-type communications (MTC) over the existing cellular networks. This Research focuses on energy consumption modeling, battery lifetime analysis, lifetime-aware scheduling, and transmit power control for massive MTC over cellular networks. Indeed, we consider a realistic model for MTC energy consumption and network battery-lifetime. Analytic expressions are derived to evaluate the impact of scheduling on both the individual and network battery lifetimes. The derived expressions are then used for uplink scheduling and transmit power control for mixed-priority MTC traffic in order to maximize the network lifetime. Besides the main strategy, low complexity analyses with limited feedback requirement are investigated, and the results are extended to existing LTE networks. In addition, the energy efficiency, spectral efficiency, and network lifetime tradeoffs in resource provisioning and scheduling for MTC over Energy-Harvesting (EH) based networks are investigated. The simulation results confirm that the proposed EH-based strategy can provide substantial network lifetime improvement and network maintenance cost reduction in comparison with the existing scheduling schemes.

Nowadays , wireless sensor networks are used in many applications for monitoring activities in different environments due to its low cost and easy communication. In these networks, sensors have access to finite energy resources, so in order to increase the lifetime of thr networks, recently, researchers are looking for ways to reduce energy consumption and therfore to increase the network lifetime. Indeed, there are some solutions to save availabe energy and maintain the performance of a wireless sensor network (WSN) in different network layers. Thus, energy harvesting (EH) is an excellent technique for increasing lifetime of WSNs and improving the shape of communicatn links via simultaneously wireless information and power transmission (SWIPT) schemes while keeping the quality of service (QoS). In this thesis, in addition to a general review for the existing methods, an EH-enabled scheme is proposed for the orthogonal frequency division multiplexing (OFDM) system, in which the power and subcarrier allocation problem is formulated to maximize the energy harvesting where quality of service (QoS) remains intact. The proposed scenarios are then extented for multi-hop communication networks .