Cell-free massive MIMO communication systems is a promising technology that uses access-points(APs) deployed throughout the coverage area instead of usual cellular systems with centralized BS to serve multiple users simultaneously. By exploiting the large number of antennas and adopting advanced signal processing techniques, cell-free massive MIMO can mitigate inter-user interference and enhance the overall system performance. Optimal power allocation plays a crucial role in maximizing the spectral and energy efficiency of wireless networks. By intelligently allocating transmit power to different users, a balance between maximizing the system throughput and minimizing the total energy consumption can be achieved. In addition, user-centric clustering(UCC) is also a key technique to improve the performance of cell-free massive MIMO systems. This technique aims to pair user equipments (UEs) with appropriate APs to facilitate efficient resource allocation and interference management. In this thesis, cell-free mMIMO communication system is investigated through user-centric clustering and power allocation. The power allocation optimization problem is formulated to maximize energy efficiency of cell-free mMIMO systems and solved by using interior-point algorithm. User-centric clustering algorithm is proposed by disabling the non-master APs that are serving only one user. This additional feature aims to reduce total power consumption of the system without sacrificing the advantages of the cell-free mMIMO communication systems. Additionally, we propose a machine learning(ML) approach to reduce the computation time required for power allocation optimization. Through extensive simulations, we demonstrate the effectiveness of the proposed algorithms in achieving significant gains in spectral and energy efficiency in cell-free massive MIMO systems. The results highlight the importance of optimal power allocation and user-centric clustering to design an efficient cell-free mMIMO systems through machine learning approach.

Over the last decade, many advancements have been made in the field of wireless communications. Among the major technology enablers being explored for the fifth-generation (5G) networks at the physical layer (PHY), a great deal of attention has been focused on millimeter-wave (mmWave) communications, massive multiple-input multiple-output (MIMO) antenna systems and beamforming techniques. These enablers bring to the forefront great opportunities for enhancing the performance of 5G and beyond-5G networks, concerning throughput, spectral efficiency, energy efficiency, latency, and reliability. At the meantime, the wireless communication is prone to information leakage to the unintended nodes due to its open nature. Hence, the secure communication is becoming more critical in the wireless networks. To address this challenge, the concept of Physical Layer Security (PLS) is explored. In this thesis, we examine the statistical mmWave transmission through linear beamforming techniques for PLS based systems. We propose the secure multiuser (MU) MIMO mmWave communications by employing hybrid beamforming at the base stations (BS), legitimate users and eavesdroppers. Using a 3 Dimensional mmWave channel model for each node, we employ the artificial noise (AN) beamforming to jam the channels of eavesdroppers and to enhance the secrecy capacity of the overall communication system. We investigate the secrecy performance on different scenarios including the single cell and multicell mmWave MU-MIMO downlink communications and reveal the key points directly related to the system security.

Wireless networks are prone to interference due to their broadcast nature. In the design of most of the traditional networks, this broadcast nature is perceived as a performance-degrading factor. However, physical layer network coding (PNC) exploits this broadcast nature by enabling simultaneous transmissions from different sources and facilitates an increase in the spectral efficiency of the wireless networks. Besides, the massive multiple input multiple output (MIMO) is considered as one of key technologies to improve the spectral efficiency for wireless communication systems. The combination of PNC and multi-user massive MIMO in the sixth generation (6G) networks can increase further the spectral efficiency. In this thesis, PNC based systems are examined via bit error rate (BER) and coverage probability by focusing on the BER of the network coded symbol (NCS). Hence, PNC based systems are compared with network coding (NC) and conventional schemes. The influence of the signal-to-noise ratio (SNR) differences of the users are examined on the BER performances. Thereby, an alternative method to estimate NCS is proposed for the MIMO-PNC systems without using log likelihood ratio (LLR). We derive a closed form expression for the coverage probability in PNC based multi-user massive MIMO systems by employing zero forcing (ZF) equalization. The non-orthogonal multiple access (NOMA) based PNC system is proposed. We show the applicability of the PNC in the NOMA based MIMO systems by giving the the BER performance results.

Millimeter wave (mmWave) communication is an advantageous technology which is capable of meeting the needs of future mobile networks. On the other hand, the propagation characteristics and system requirements are the restrictive factors for utilization of mmWave communication. Hybrid and digital beamforming architectures can be evaluated as worthy candidates to utilize mmWave communication. In the hybrid architecture, selection of a few number of beams by exploiting the sparse structure of the beamspace channel provides high spectral efficiency with low complexity. In this thesis, the multi-user mmWave communication in sparse and dense environments are investigated. Beam selection algorithms presented in the literature are performed for the sparse environment. While the number of users is equal to the number of radio frequency (RF) chains in a sparse environment, the number of RF chains is less than the number of users in a dense environment. Therefore, an algorithm which performs beam and user selection for the dense environment is proposed. The user selection in the proposed beam and user selection algorithm is performed based on the correlation among users’ channels. Since the users’ channels are highly correlated in mmWave communication, the proposed beam and user selection algorithm improves the spectral efficiency considerably. Furthermore, a non-uniform rectangular array (NURA) antenna configuration for mmWave communication is investigated when the digital beamforming architecture is employed. Then, a user selection algorithm is proposed under the case of lower number of antennas. The simulation results demonstrate the improvement in sum data rate through the proposed user selection algorithm in mmWave communication with NURA configuration.

Device-to-device (D2D) communication provides an effective way to meet growing mobile traffic and capacity demand. D2D communication can improve existing cellular systems in several ways. When UEs are located in close proximity, they can communicate through direct links bypassing the base station (BS). In this way, the transmitter consumes less power while better Quality-of-Service can still be provided. D2D links can also increase both energy and spectrum efficiency by reusing downlink and uplink cellular resources. However, integrating D2D links into the cellular infrastructure complicates the interference situation because D2D communication might increase the co-channel interference and degrade cellular link quality. In this thesis, the interference mitigation techniques including resource allocation, power control and multiple antenna are proposed for D2D communications underlaying cellular systems to increase the data rate of both the cellular users and D2D pairs. The Zero-Forcing technique is carried out for interference mitigation by assuming perfect channel state information at the BS side. The effect of a limited feedback link for downlink cellular communication and channel estimation for uplink communication are considered for underlying multi antenna cellular system.

In the last decade, the demand for wireless services increases at unprecedented rates. Due to the inherent open nature of radio propagation, wireless transmission is vulnerable to various attacks despite its popularity. Therefore, communication security in wireless networks is becoming more critical than ever. Conventionally, cryptographic techniques are deployed on upper layers of network protocols as a solution. As a complement to the traditional cryptographic techniques, physical layer (PHY) security exploits the characteristics of wireless channels to enable secure wireless communications. The aim is to limit the amount of information that can be extracted by any unauthorized users via utilizing inherent randomness of noise and communication channels. The design of PHY security schemes is not based on the premise that eavesdropper has limited computational power contrary to upper layer secrecy techniques. In fact, the eavesdropper may have infinite computational power. Nevertheless, secure communication can be achieved by the combination of appropriate coding and transmit precoding design with the usage of available channel state information. PHY security methods can work independently from upper layer encryption techniques. Thus, PHY security techniques can be used to leverage the secrecy of already existing communication systems. In this thesis, PHY security enhancement mechanisms, especially in multiuser multiple antenna systems with a limited feedback link are investigated. Four different system models under secrecy consideration with different channel conditions including quasi-static fading channels, temporally correlated fading channels are presented. In order to disrupt the reception of any potential eavesdropper, artificial noise (AN) beamforming scheme is employed. The effects of lack of perfect channel state information (CSI) at the transmitter and the AN leakage that is caused by limited CSIT are analyzed. The thesis proposes a reduction in feedback load using receiver side selection criterion with special codebook design and appropriate beamforming. Our approach is capable of enhancing the security of wireless communications by selecting the users with favorable channel conditions and quantizing channel direction information (CDI) by a special codebook. Also, inter-user interference is utilized as a jamming method when eavesdropper’s CSI unknown by the transmitter. Simulation results demonstrate the feasibility of the proposed PHY security mechanisms by examining the achievable secrecy rates.

Since the interest in mobile communication sector is increasing day by day, it makes traffic volume problem more important. There are different works focused on developing more secure and qualified service for professional users and companies. The Professional Mobile Radio (PMR) system, specially developed for professional users in the communication sector, can be offered to the service of professional users and companies with the desired specifications. With the Tetra system, which is one of the PMR systems, users can get more advanced technological services than the conventional PMR systems. Cell selection algorithms have a great importance for these systems which are needed for more reliable, private and seamless communication. In this thesis, we present two novel cell selection algorithms that can be applied to the Tetra based PMR systems. In these algorithms, both the received power of users and the fair distribution of the overall system are considered. Performance evaluation of algorithms with different traffic characteristics is considered in different environments.

Public safety organizations provide a stable and secure environment for the society. Wireless communication between public safety officers is very important to transmit voice or data during an emergency crisis. When the public communication networks can not provide service during crisis, disaster and high traffic cases, Professional Mobile Radio systems (PMR) such as conventional Association of Public Safety Communications Officials (APCO25) and trunked Digital Mobile Radio (DMR) systems are needed to improve the service quality and to provide uninterrupted service provided to the users. While providing continuous voice and data service, it is very important to efficiently select the base station to be served and to ensure that a mobile user can seamlessly attach from one base station to another base station while moving within a cell. In this sense, it is critical to determine the base station to be served by efficient cell selection algorithms. Cell selection is the process of deciding the base station which provides services to the users. Cell selection plays an important role in balancing the system load and thus overall system performance. By means of efficient cell selection algorithms, it is aimed to reduce the waiting time and to connect a base station as soon as possible while establishing reliable transmission link for PMR systems in emergencies. In this thesis, the full set and the reduced set based cell selection algorithms are proposed by considering load based and traffic based cell selection algorithms. In load based cell selection algorithm, each user selects the base station according to the calculated utility value determined based on both received signal strength indicator (RSSI) value and cell load information. In addition, it is performed that each user selects the base station according to the calculated utility value determined based on both biased signal to interference plus noise ratio (SINR) value and cell load information. In traffic based cell selection algorithm, while calculating cell load information, traffic intensity is considered. The performances of the proposed algorithms are evaluated based on with various scenarios by taking into account different performance metrics for conventional APCO25 and trunked DMR systems.

Since traffic diversity and volume increase with growing popularity of mobile applications, there is the strong need to manage the traffic carried by networks. Software defined networks can simplify network management while enabling new services by employing traffic management including routing whose goal is to maximize the given utility while satisfying capacity requirements. Another key concept to meet up huge data traffic is cloud-based radio access networks. By integrating cloud services to radio access networks, operators will make use of network functions virtualization which allows to host different virtualized functions on a common hardware platform. In this thesis, an efficient routing algorithm is proposed to minimize the cost based on power consumption determined by the number of active OpenFlow switches and active links in a software defined networks while satisfying throughput requirements of all flows according to constraints on link capacities in the software defined mobile network. The algorithm is also implemented in mobile network by combining resource allocation in a cloud radio access network. The performance of the proposed algorithm is evaluated based on power consumption efficiency for different network topologies with various scenarios.

There has been a tremendous increase in the usage of multimedia services with the rapid penetration of mobile devices. In parallel to the technological developments in hardware and software of communication devices, users demand to have higher quality and more reliable services. The developments in network technologies are towards forming a converged structure that mobile, fixed and internet access technologies are able to operate together. Heterogeneous wireless networks have a critical role in order to meet dramatically increasing traffic demand. As a result of better operation of the systems with the help of heterogeneous wireless networks, it is possible to serve subscribers with higher performance with the help of offloading which transfer the traffic load from a network to another one. Various strategies are used in order to offload traffic between different wireless communication technologies. The main objective of this thesis is to examine offloading strategies which provides operation of different wireless communication technologies efficiently in heterogeneous wireless networks. The performance evaluations of different offloading strategies in various scenarios are implemented. The comparisons of strategies which are user initiated and network initiated are provided by considering their overhead load.

The need for high capacity and data rate increases with the growing demand for wireless communication. In order to meet this demand, one of the most effective ways of improving capacity and data rate is d deployment of femtocell networks which are considered to be a promising technique for future wireless networks. However, mass deployment of these low – power base stations brings many challenges. Interference management will be one of the major challenges for the dense deployment scenarios of femtocells in coverage of the macro base stations. To cope with interference problem, there are many interference management techniques. In this thesis, power control and beamforming techniques are implemented separately and jointly in order to deal with cross-tier downlink interference which occurs between macro base station and users of femtocell. In this two-tier network system involving femtocell and macrocell layers, power control problem, first, is investigated. Feasible transmission power r region for femtocell is determined with respect to the user locations so that targeted signal – to – interference – plus – noise – ratio (SINR) values are satisfied. Secondly, beamforming technique is applied using partial zero-forcing method. In this method, beamforming vectors are designed to remove cross-tier interference. It is observed that SINR of macro base station’s user does not undergoes any degradation in the nearfield region of femtocell. Finally, we apply these two techniques jointly. Since both interference suppression and power – efficiency is provided, joint technique seems to be a viable and environment-friendly solution for femtocell networks.

The rapid growth of traffic demands during past years, has led to the immense deployment of heterogeneous wireless networks consisting large-scale macro cells overlaid with multiple tiers of small cells. This is conceived as the major capacity and performance enhancement coordinator by means of increasing the spectral efficiency per unit area. However, heterogeneous networks implementation comprises new technical challenges related to interference issues and throughput deterioration. Advanced interference coordination techniques are introduced to handle these challenges. The usage of range expansion allows captivating more users and hence attaining performance improvement, however causes extra downlink interference. This becomes exquisite for higher bias values; hence the benefits convert into significant deterioration. To overcome these issues, range expansion should be jointly designed with inter-cell interference coordination. The main objective of this thesis is to analyze the concept of heterogeneous network, the cell selection strategies including range expansion, interference coordination schemes and energy efficiency. The performance evaluations are obtained to different macro-pico base stations deployment scenarios for heterogeneous network by using various cell selection algorithms with and without interference coordination depending on frequency allocation schemes to figure out their impact on the system performance for different contours.

As a rapidly growing network UMTS, the 3rd generation mobile communication system, is designed to provide sufficient capacity for the services requiring high bit rates. The WCDMA technology has been chosen for the technique of UMTS in which all connections are able to use the same frequency band and time thanks to orthogonal and pseudorandom codes. As a result of using the same frequency band, interference management is a key in optimizing the network capacity and coverage. Therefore, a practically applicable algorithm is needed. However, the existing algorithms generally present iterative methods which are difficult to be applied for mobile network operators in that iterative methods require more man power and increase costs. In this thesis, we present a two-step method that will decrease interference in UMTS Networks according to received power measurement results and network initial configuration by adapting antenna tilt, azimuth and Common Pilot Channel (CPICH) power since those parameters have direct impact on coverage area in terms of shape and size. First step calculates base stations antenna downtilt and CPICH power while second step adopting azimuths. The performances of proposed algorithms are obtained considering practical scenarios. The results have shown that antenna tilt, pilot power and azimuth can be used successfully in managing interference for UMTS Networks.

The wireless cellular networks are limited by interference and coverage issues where the users at the edge of the cell usually do not receive enough signal energy. To combat these problems and provide higher signal to interference noise ratio and capacity without increasing transmit power, the idea of using relays in cellular networks was explored and evaluated in the literature. On the other hand, multiple input multiple output (MIMO) antenna systems have great potential to increase capacity and reliability of a wireless cellular network compared to single input single output systems. Hence, the integration of MIMO systems in the relay-based cellular networks has great potential to meet the growing demands of future communication. In this thesis, we explore the performances in conventional and relay-based wireless systems with single and multiple antennas by adjusting the frequency reuse factor as one and four. We consider wireless cellular based networks where six fixed relays are placed evenly in each cell in a hexagonal layout. A user chooses to receive the transmitted signal either directly from the base station or via one of the relays by employing selection algorithms. Throughout this thesis, we first determine the optimum relay locations considering different relay powers. Then, we investigate the system capacity for the cell with and without relays. Next, we examine the capacity performances by changing the cell diameter and the relay power. Finally, we explore the performances of relay based networks with multiple antennas.

The aim of this study is to focus on spectrum sensing in cognitive radio which is a recently introduced technology in order to increase the spectrum efficiency. Increasing efficiency of the spectrum usage is an urgent need as an intrinsic result of the rapidly increasing number of wireless users and also the conversion of voice oriented applications to multimedia applications. Static allocation of the frequency spectrum does not meet the needs of current wireless technology that is why dynamic spectrum usage is required for wireless networks. Cognitive radio is considered as a promising candidate to be employed in such systems as they are aware of their operating environments and can adjust their parameters. Cognitive radio can sense the spectrum and detect the idle frequency bands, thus secondary users can be allocated in those bands when primary users do not use those in order to avoid any interference to primary user by secondary user. There are several spectrum sensing techniques proposed in literature for cognitive radio based systems. In this thesis, energy detection and cyclostationary feature detection based spectrum sensing systems for cognitive radios with and without multiple antenna are examined in detail and comparative performance results are obtained in wireless communication channels.

Orthogonal frequency division multiplexing (OFDM) is well-known for its efficient high speed transmission and robustness to frequency-selective fading channels. On the other hand, multiple-input multiple-output (MIMO) antenna systems have the ability to increase capacity and reliability of a wireless communication system compared to single-input single-output (SISO) systems. Hence, the integration of the two technologies has the potential to meet the ever growing demands of future communication systems. In these systems, channel estimation is very crucial to demodulate the data coherently. For a good channel estimation, spectral efficiency and lower computational complexity are two important points to be considered. In this thesis, we explore different channel estimation techniques in order to improve estimation performance by increasing the bandwidth efficiency and reducing the computational complexity for both SISO-OFDM and MIMO-OFDM systems. We first investigate pilot and Expectation-Maximization (EM)-based channel estimation techniques and compare their performances. Next, we explore different pilot arrangements by reducing the number of pilot symbols in one OFDM frame to improve bandwidth efficiency. We obtain the bit error rate and the channel estimation performance for these pilot arrangements. Then, in order to decrase the computational complexity, we propose an iterative channel estimation technique, which establishes a link between the decision block and channel estimation block using virtual subcarriers. We compare this proposed technique with EM-based channel estimation in terms of performance and complexity. These channel estimation techniques are also applied to STBC-OFDM and V-BLAST structured MIMO-OFDM systems. Finally, we investigate a joint EM-based channel estimation and signal detection technique for V-BLAST OFDM system.