To address the problem of radio spectrum congestion due to increasing demand for wireless communications services, cellular communication systems are going towards small cells with small transmit powers. At the same time, in-band fullduplex (FD) radio design has gained considerable attention due to achievements in signal processing that can make design of full-duplex radios possible for systems with small transmit power. In theory full-duplex radios can double the spectral efficiency of the system. However existing radios still do not provide enough self-interference (SI) cancelation to be used in large transmit power systems. Meanwhile device-to-device communication (D2D) is seen as a promising idea to increase the performance of wireless networks. In D2D, users in vicinity communicate directly without going through base station. So far, very limited work has been carried out to study the applicability of available full-duplex radios in D2D. In this thesis, we investigate full-duplex D2D and amount of self-interference cancelation required in D2D in cellular systems. While D2D users share the same radio resources with cellular users, both cellular and D2D pair will receive interference. Resource allocation and interference management become crucial in D2D communication. Both uplink and downlink resource sharing are considered. In uplink resource sharing, to handle the interference on the base station power control is used in D2D transmitter. To deal with the interference at D2D receivers from cellular user’s uplink transmission, interference-limited-area (ILA) method is used to select users with negligible interference on them. When D2D pair is using downlink resources of cellular users, users receive interference from D2D transmissions. Limiting this interference is also done using ILA method. On the other hand, for the purpose of resource sharing, the user with smallest downlink transmit power is selected to minimize the interference on D2D receivers. Half-duplex (HD) and full-duplex D2D scenarios are considered in both uplink and downlink resource sharing. Simulations show that how much of self-interference cancelation is required in different scenarios. Effects of the numbers of the selected users for resource sharing, distance between D2D users and also inter-cell interference is studied. It can be concluded that using available full-duplex radios in D2D communication can almost reach the theoretical doubling of throughput in full-duplex mode compared to half-duplex mode.

Medical ICT applications have developed significantly during the past years. In particular, wireless and mobile communications have provided healthcare with efficient, flexible and cost-effective solutions. Mobile networks can be used as the infrastructure supporting remote monitoring of patients. However, wireless and mobile networks are inherently unreliable, while medical ICT applications must be highly reliable. Mobile Cloud (MC) is a new and promising paradigm, which allows proximate mobile users to establish short-range connections as well as being connected through their cellular access. A mobile cloud is defined as an opportunistic cooperative cluster of wireless devices in close proximity (i.e., short-range), where each device can also be connected to access points or base stations, even simultaneously. A mobile cloud can be utilized as a possible communication technology to provide high reliability data transmission on health monitoring devices. This new paradigm is proposed to minimize the outage probability by the cooperative diversity offered by the collaborative devices in the cloud. Most of the prior works on MC are focused on the energy efficiency improvement in the nodes of mobile clouds. Four medical ICT scenarios are considered that can use mobile clouds to improve the reliability of data transmission in this thesis. The proposed scenarios are classified based on their typical use and key communication requirements. A Wireless Body Area Network (WBAN) monitors the health or wellbeing condition of the user. Moreover, a mobile or smart-phone owned by the user/patient acts as a gateway device which collecting the measured data from the WBAN. The monitored user exploits a MC with other communication-enabled devices in its close proximity. The studied MC is operated in a single-cell involves cellular users and one BS. The Selection Amplify-and-Forward (S-AF) and All-participate Amplify-and-Forward (AP-AF) cooperative algorithms are proposed to minimize the outage probability of the system. In the S-AF case, the best node with highest transmitted SNR is selected and retransmits the data. The selection is done at the BS side. The AP-AF algorithm uses all the cooperating devices in the cloud for relaying the data. Both algorithms applied TDMA fashion for relaying the signal. The performance of the proposed algorithms is compared with the non-cooperative transmission link. Simulation results illustrate that the offered MC model is capable to achieve significant performance gains over the non-cooperative case in terms of outage probability. Results also show that the outage probability is highly affected by the cloud size in both approaches. The S-AF scheme offers the best performance in minimizing the outage probability compared to the AP-AF and non-cooperative cases.

Telecommunication industry has experienced a major breakthrough in the last few decades due to the immense development in information technology. Ubiquitous connectivity, expeditious increase in the number of low cost yet powerful smart devices and quantum leap in social networking are posing new challenges to cope up with the current as well as future requirements. While substantial amount of work has been done in this context, particularly on cooperative and cognitive networks, the very approach has certain limitations and shortcomings. The three characteristic challenges are enhance system throughput, dynamic environment adaptability and productive utilization of the available resources. Here we present mobile cloud, a novel yet simplistic system model that employs cognitive and cooperative strategies to address all of these three challenges. The system exploits the short range link to establish a small social network among the nearby devices, adapts according to environment and uses various cooperation strategies to obtain efficient utilization of resources. Lastly, we implemented an experimental mobile cloud and attentively assessed its performance with varying parameters and legacy approach used in the similar context. The analysis provided sound understanding of system model compliance with the primary objectives as well as with the future networks.

Congestion in wireless sensor networks (WSNs) has always been a serious problem for all kinds of communication networks. It causes severe information loss and shortens the life time of the sensor nodes. Congestion also leads to excessive energy consumption due to large number of retransmission and packet loss which lowers throughput. In WSNs congestion need to be controlled in order to have high energy-efficiency, to prolong system life time, improve fairness and improve quality-of-service in terms of packet loss ratio with the packet delay and link utilization. Most of the designs of WSN depend on the applications and the environment in which the sensor nodes are deployed. It has important applications such as remote environment monitoring, target tracking, military and surveillance, etc. The placement of the nodes is often done randomly or in a pre-planned manner. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. WSNs can be an event driven which can be routed to detect or monitor data at the base station depending on their degree of priority since the data in the sensor networks has different importance. WSNs face challenges in dealing with the issues of congestion due to their constraint nature and complex algorithms. During the last decade, the tremendous congestion control algorithms and schemes have been proposed to solve the issue of congestion by ensuring fair delivery of packets to the base station. This thesis explores the different congestion detection algorithms and schemes, which are especially targeted for the WSNs and presents a survey of congestion control mechanisms used in WSNs. In addition, the study in this thesis would find out the common features which may help in the future research.

This thesis analyzes a scenario where the distribution system operator needs to estimate whether the average power demand in a given period is above a predetermined threshold using a 1-bit memoryless scheme. Specifically, individual smart-meters periodically monitor the average power demand of their respective households to inform the system operator if it is above a predetermined level using only a 1-bit signal. The communication link between the meters and the operator occurs in two hops and is modeled as binary symmetric channels. The first hop connects individual smart meters to their corresponding aggregator, while the second connects different aggregators to the system operator. In the first set of analysis, the decision making only happens by the network operator in the second hop and aggregators in the first hop only work as relay nodes which only forward the information it has received from the smart meters. AND and OR decision rules are studied in this scenario. Moreover, in the second set of analysis, the decision about the power demand happens in two stages based on the received information bit. Meaning that the decision making happens both by the aggregators in the first hop and network operator in the second hop. We consider here three decision rules in the second scenario: AND, OR and MAJORITY. Our analytical results indicate the circumstances (i.e. how frequent the meters experience the consumption above the defined threshold) and the design setting (i.e. decision rules) that a low error probability can be attained. We illustrate our approach with both theoretical and numerical results from actual daily consumptions from 12 households and 3 aggregators. Also, we derive closed-form equations for the average decision error probability as a function of the system parameters (e.g. number of sensors, communication error, sensing error) and the input signal characterization. The first set of simulations are done in Matlab. Since the second set of data are provided in Excel; thus, the simulations are done using Visual Basic.

This thesis is about testing a system’s actual performance under the IEEE 802.15.4-2011 UWB specifications, with a compliant device DW1000. It is of great interest to test the synchronization ability of different preamble lengths, which are applied in the IEEE 802.15.4-2011 UWB standard. It is also urgent to know the system’s actual performance in a multipath propagation environment, since the IEEE 802.15.4-2011 UWB standard allows an energy detection (ED) receiver to take advantage of multipath propagation. Theory predicts that a long preamble length can offer better synchronization ability at long distances, and has a longer working range. On the other hand, a long preamble length requires a longer channel occupancy time and more power consumption. Thus, a long preamble may not be the optimal choice for working at short distances. The channel model of the IEEE 802.15.4-2011 UWB standard, which is based upon the Saleh-Valenzuela (S-V) model, can be regarded as block fading. Although multipath propagation can improve the system’s performance by increasing the SNR, the effects of block fading on the system must be taken into account as well. It is pointed out in various papers that the S-V model is precise in predicting a none-line-of-sight (NLOS) environment, while it is not precise in predicting a line-of-sight (LOS) environment. The results of the first part of the measurements show that longer preambles have longer working ranges. However, the longer preambles’ performance, in the term of the packet reception ratio, is not necessarily better than that of the shorter preambles. The results of the second part of the measurements show that the system can take advantage of multipath propagation. On the other hand, the system’s performance might become instable, due to block fading. The receiver and the transmitter will have difficulty in synchronization, if the channel impulse response changes too much within the unsynchronized time period. A longer preamble length tends to offer a longer stable working range. In addition, the path loss of the channel will suddenly increase and then decrease. This phenomenon of a sudden change in the path loss at a certain distance is quite similar to that of a narrowband system.

In this thesis, a steerable antenna system which is able to maintain high connectivity through beamforming towards the strongest base station signal is presented. Main objective of the thesis is to design an antenna system for vehicles operating in poor coverage region or even in no coverage region, in order to enable these vehicles to make a reliable communication link with far away base stations. To achieve this high performance antenna system, several antenna designs were considered and evaluated for their performance. This thesis provides an overview of different antenna designs considered and their pros and cons. Among these designs, the concept of stacked patch antenna was selected for prototype manufacturing because of its good performance in terms of bandwidth, efficiency, gain, impedance matching and ease of fabrication because of its simple structure. Stacked patch antenna was optimized for lower GSM band covering frequencies from 824 MHz to 960 MHz by using electromagnetic simulation software CST Microwave Studio. Finally the stacked patch antenna was fabricated and measurements were performed. The results for both the prototype measurement and simulations are presented and compared. From the comparison, it is concluded that the manufactured antenna element prototype gives high performance as promised by simulation results and is suitable for the adaptive vehicular antenna system.

The usage of massive antenna arrays coupled with millimeter-wave (mmW) transmissions has emerged as enabling technology of the fifth generation mobile communication standard, the 5G. This solution has great potentials to provide Gb/s data-rate and high cell capacity by leveraging the synergy amongst high resolution spatial filtering, adaptive beamforming and channel sparsity. One of the main challenges, however, is related to the implementation and digital processing as with a conventional transceiver architecture, an increase of the number of antennas implies more analog-to-digital (or digital-to-analog) converters, more power amplifiers and baseband units. Subsequently, the energy, factor-size and computational power requirements become impractical. To counter these effects a hybrid transceiver design has been proposed, in which multiple analog front-ends are combined into a single (or multiple) baseband processing unit allowing the transceiver to reduce the complexity of the digital signal processing as well as the power consumption. In this Thesis we investigate different architecture models and evaluate the trade-off between energy consumption and performance in channel estimation. More specifically, we study a hybrid receiver model with 64 antenna elements, parallel digital paths and, for the channel estimation, we consider the adaptive-least absolute shrinkage and selection operator (A-LASSO) algorithm that leverages channel sparsity into the estimation. Simulation results have shown that a transceiver architecture with only four base-bands performed best over the different cell sizes. Compared to the fully digital receiver this results in tenfold power consumption reduction according to analysis.

Efficient use of wireless spectrum is needed, due to enormous increase in wireless devices during last few years. In this context lot of effort is being done to make an intelligent and cognitive radio system, which can use the spectrum opportunistically. The ratio of the signal average power to the interference plus noise average power is called signal to interference plus noise ratio (SINR). SINR is one of the important parameters that can help in developing cognitive radio systems, because on the basis of its calculation the spectrum can be utilized efficiently. The principle goal of this thesis is to implement a SINR estimation algorithm for a cognitive radio network (CRN) test-bed. The proposed SINR estimation algorithm is second order moment and fourth order moment (M2M4) SINR estimation algorithm, where M2 and M4 are the second order moment and fourth order moments respectively. The M2M4 estimation algorithm is one of the non-data-aided (NDA) estimation algorithms. Hence, the algorithm takes the received signal as input and calculates the second and fourth moments blindly. The average signal power and average interference plus noise power can be calculated from these second and fourth order moments, their ratio yields the SINR. The M2M4 estimation algorithm is first simulated in MATLAB, and then it is designed for system generator model to draw fair comparison between simulations and system generator model. The experimental evaluation revealed that despite of the word length constraint in the system generator model, it performs reasonably well when compared to the ideal (MATLAB) solution. The M2M4 estimation algorithm is tested and verified by different test cases, to ensure its validity. The algorithm is tested for different signal strengths. The result shows M2M4 is an efficient algorithm for the SINR estimation. However, the proposed architecture could not fit into the aimed hardware because of heavy design since it consume more resources than available.

Multi agent system (MAS) is considered an effective way to design, analyze and implement complex systems in various disciplines nowadays. However, MAS has not been sufficiently applied in mainstream modelling of wireless communication networks yet. The exponential growth of network users has led today’s communication networks even more significantly complex. As such, modelling and simulation tends to grow in proportion but not markedly to meet the preciseness and complexity of the system under consideration. Furthermore, the future mobile communication seems to incline over self-adaptive resource allocation and congestion control mechanisms. This aims to relieve the workload of the network operator while maintaining the QoS level of the communication intact. The advancements also envision the autonomous nature of future wireless communication technologies where dynamic resource allocation will play a vital role in efficient bandwidth utilization, throughput maximization and effective power control mechanisms. In this context, MAS brings about various possibilities to model and simulate environments which are typically stochastic in nature and tends to grow in a decentralized manner. MAS based simulation is such a simulation method which has gained recognition in modeling telecommunication systems where issues like network complexity, traffic and network management are prevalent. MAS has its proven standing to represent a real interactive environment of a system where learning, negotiation and cooperation are important phenomena. On that account, MAS has already started to establish its turf in the wireless communication systems as well. As a matter of fact, the existing network simulators are not designed to incorporate the features that MAS has to offer. So, the agent based simulation toolkits are used alongside, on top of which most of the physical environment aspects can be modeled that are usually neglected by the existing network simulators. This thesis investigates the areas of wireless communications where multi agent systems and simulators are applicable by the means of literature study and presents simple simulation models constructed in Netlogo, a multi agent based simulation toolkit. As a result, the applicability of MAS simulators in areas like radio channel environment, resource allocation, routing, medium access control and cognitive radio is presented. At the end, conclusions are drawn about feasibility of using MAS simulators to simulate wireless communication networks.