Ever evolving wireless communication standards, reduced time-to-market and a need for flexibility and interoperability of multiple wireless communication technologies on a single device are the driving factors behind implementation of wireless standards on Software Defined Radios (SDR) platforms. The concept behind SDR is to implement as much functionality on software as possible. SDR provide greater interoperability and programmability compared with traditional hardwired implementation at the cost of higher power consumption and market cost. SDR is the driving technology for the next generation of co-operative and cognitive radios. For implementing an SDR, the existing wireless communication algorithms needs to be modified and an appropriate hardware platform needs to be selected. The IEEE 802.15.4 LR-WPAN standard requires low cost and low-power consuming devices. The data rate requirements are also low (such as 250 kbps). Traditionally, the devices compliant with the standard are hardwired system-on-chip implementation which provides benefit in terms of power and cost. Recently, there has been significant effort on modeling the IEEE 802.15.4 SDR systems which provide greater interoperability and programmability of the devices. In this study, Transport Triggered Architecture (TTA) based Application Specific Processor is selected for SDR implementation of the IEEE 802.15.4 2.4 GHz physical layer for studying the performance of such system in terms of Bit-Error-Rate, CPU cycle count, and processor chip area. As part of this work, different SDR frameworks like GNU Radio, Matlab-Simulink etc. were evaluated for their feasibility of providing an agile platform for the development. These existing frameworks need an operating system for their execution and are not suitable for stand-alone systems such as a TTA based processor. The work also includes the study of different receiver algorithms and design choices for the transceiver implementation. Based on existing literature and Matlab modeling, Asynchronous Zero-Crossing Detector (AZCD) based non-coherent receiver algorithm is selected for the implementation. The algorithm provides the required BER performance with very less complex computation and is suited for low power and low chip area implementations. The transmitter and receiver are implemented on single-core TTA processors which provide the required performance in terms of BER and data throughput. The processors designed need a very low silicon area and clock frequency for their realization.

Since the integration of data services into cellular communications, cellular operators are struggling to harness the overwhelming data traffic on their networks. Underlay Device-to-Device (D2D) communication is a new and promising paradigm which allows proximate mobile users to have direct communication over the cellular spectrum that may be reused by other cellular users in the same cell. This new paradigm is proposed to assist the cellular operators to deal with the booming demand of mobile users. Recent studies have shown that underlay D2D communication significantly increases the cellular network capacity, and enables cellular operators to support rich multimedia services. However, reusing cellular resources for both D2D and cellular communication introduces interference issues. In such systems, interference management is of utmost importance because improper interference coordination may lead to a self-destructive network. Power control and beamforming appears to be viable techniques for interference management which can also be used to enhance the energy efficiency of the system. Network coordinated sum power optimization schemes for D2D communications underlaying uplink and downlink cellular spectrum is considered in this thesis. In particular, the system optimization target is to minimize the sum transmission power while guaranteeing the user specific rate constraints. Novel algorithms are proposed to solve the power minimization problem optimally. For the uplink, the problem is solved using joint transmit power control and receive beamforming algorithm. The downlink problem is reformulated as a second-order cone program (SOCP), and thus, it can be solved efficiently via standard SOCP solvers. Moreover, a decentralized algorithm is proposed that reduces the amount of control information exchange in comparison to the centralized approach. The performance of the proposed algorithms is compared with the conventional cellular scheme. Simulation results demonstrate that the proposed underlay D2D communication approach is capable of achieving significant performance gains over the conventional cellular scheme. Results also illustrate that the power consumption of the system is highly affected by the location of the interfering cellular user and whether the resources are shared in uplink or downlink. Therefore, four different resource sharing areas are defined for D2D communications. These areas specify the type of resources (i.e., downlink and uplink) suitable for D2D communication.

In the uplink channel of the 3GPP long term evolution (LTE) and LTE-Advanced (LTE-A) systems, signal carrier frequency-division multiplexing access (SC-FDMA) transmission scheme is employed instead of orthogonal frequency-division multiplexing (OFDM) to reduce the peak-to-average power ratio (PAPR). However, compared to OFDM, SC-FDMA has lower channel throughput, since it suffers from inter-symbol interference (ISI). Multi-rate equalizer (MRE) is a novel low complexity and non-linear equalizer which can increase the channel throughput. The basic idea of the MRE is that it first decomposes the single ISI channel into two parallel sub-channels by employing multi-rate signal processing and successive interference cancellation (SIC). Then, this decomposition procedure can be executed recursively to further increase the number of sub-channels. The ISI decreases as the number of sub-channels increases. Meanwhile, since the MRE does not require pre-coding, it does not increase PAPR. The practical implementation of the MRE is not straightforward. An algorithm, which can recursively call each function block in the MRE and execute the entire decomposition processes is required. In this thesis, an algorithm is developed based on the construction pattern of the MRE to enable its realization. An LTE standard-compliant turbo code is simulated to evaluate the practical performance gains of the MRE concept. MATLAB is selected as the simulation environment. According to the simulation results, the channel throughput can be increased by employing the MRE together with LTE turbo code indeed. One time-invariant and one time-varying channel model are employed. Three kinds of MRE with binary modulation are considered. Those are the MRE with two, four and eight sub-channels. The increase in throughput is at least 25% and can reach 80% in highly frequency selective scenarios.

Emergence of dramatic increase in applications provided by smart devices, such as smart phones, is no longer supported by traditional telecommunications systems such as wireless cellular systems. Arising challenges are ever increasing traffic demand, shortage of available spectrum and congestion over wireless systems. On the other hand, network resources such as spectrum and computational capability, are severely under-utilized. With regard to efficient use the available resources, promising trend is to develop heterogeneous networks (HetNets) such that different operators can share their excess capacities among themselves with the previous agreement. The most research done in spectrum sharing is focused only on the network access point. In this thesis work we extend the modelling of the spectrum sharing problem to include all links on the route for a given session. While this problem might have been analyzed from the point of view of route availability our control system is focused on queue management across the network that maintains predetermined spectra sharing rules at the session level of each operator. Addressing an issue of congestion over wireless system different congestion control mechanisms are presented and analyzed enabling a variety of options for managing traffic across the spectra sharing network. These models are generalized to include different pricing mechanisms. Two approaches are taken for analyzing pricing models with congestion control mechanism. First, network nodes are modeled as two-dimensional Markov processes. Since memoryless nature of Markov process imposes restrictions on analyzed system, in order to generalize analysis, averaged non-Markov models are introduced. Performance metric used for assessing different models is average packet dropping rate.

This thesis investigates the power allocation scheme and essential design constraints to be considered in multicarrier systems particularly in the case of orthogonal frequency division multiple access (OFDMA) system in multiuser (MU) scenario. The compatibility between multicarrier system and multiple input multiple output (MIMO) system is exploited in designing the power allocation algorithm for a cellular network with multiusers. The multicarrier MIMO system facilitates dynamic resource allocation due to the decomposition of physical resources into multiple domains. The energy efficiency and interference management are the crucial aspects especially in uplink (UL) transmission. Limiting the power consumption of mobile terminals (MT) in uplink (UL) is inevitable due to the limited amount of available energy. Furthermore, the traditional multicarrier system introduces a dynamic peak power variation with respect to average power causing erroneous circuit behavior. This phenomenon is usually quantified as peak to average power ratio (PAPR). High PAPR drives the high power amplifier (HPA) into non-linear region to result in significant degradation in the system performance in terms of power efficiency. In this thesis an iterative power allocation algorithm is proposed to minimize the sum power and PAPR. This thesis presents the power allocation strategy such that the PAPR is controlled during the power allocation (minimization) stage in frequency domain. The optimal power allocation is achieved by joint optimization of transmit power and receive beamformers (TX-RX) using convex optimization technique. The original problem is not jointly convex with respect to TX-RX. Therefore an iterative algorithm is proposed to optimize TX and RX alternatingly such that by calculating TX for given fixed set of RX and vice versa until convergence. The statistical approach is adopted to reduce the PAPR by actually minimizing the signal power variance (SPV) due to the fact that the large number of independent and identically distributed complex OFDMA symbols tends to follow Gaussian probability density function characterized by certain mean and variance. The non-convex constraints in the formulation are transformed into convex form using the successive convex approximation (SCA) with required change of variable (COV). The algorithm guarantees to maintain the user-specific quality of service (QoS) defined by the rate constraint. Hence, equipped with the potentials of future generation technologies and using convex optimization as a tool, this thesis offers a sum power and PAPR minimization scheme for MU SIMO-OFDMA UL transmission.

We analyze the performance of dual-hop multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay systems by considering the source-to-relay and relay-to-destination channels undergo Rayleigh and Rician fading, respectively. Several MIMO techniques and practical relaying scenarios are considered to investigate the effect of such asymmetric fading on the MIMO AF relaying systems. First, we investigate the performance of the optimal single stream beamforming on non-coherent AF MIMO relaying. We use tools of finite-dimensional random matrix theory to statistically characterize the instantaneous signal-to-noise ratio (SNR). The closed-form expressions of the cumulative distribution function, probability density function, and moments of SNR are derived and used to analyze the performance of the system with outage probability, bit error rate (BER), and ergodic capacity. Numerical simulations are carried out to investigate the effects of the Rician factor, rank of the line-of-sight (LoS) component, and the number of antennas at the nodes on the system performance. Additionally, the performance is compared with orthogonal space-time block-coding (OSTBC) based AF MIMO system. Next, we investigate relay selection schemes for non-coherent dual-hop AF relaying with OSTBC over asymmetric fading channels. We propose two relay selection methods as optimal and sub-optimal schemes. The performance of proposed schemes are discussed with respect to the outage probability, BER and the ergodic capacity. Finally, we study the effect of co-channel interference (CCI) and feedback delay on the multi-antenna AF relaying over asymmetric fading channels. Here, transmit beamforming vector is calculated using outdated channel state information due to the feedback delay from relay-to-source, and the relay node experience CCI due to frequency reuse in the cellular network. The performance is investigated using the outage probability, BER and ergodic capacity to analyze the effect of the Rician factor, CCI, feedback delay and number of antennas. All these discussions are useful to evaluate the performance of AF MIMO systems in asymmetric fading channels. Our analysis suggests that having good LoS component increases the performance of the system for multiple-input-single-output (MISO) and single-input-multiple-output (SIMO) scenarios of relay-destination channel. Having good scattering component increases the performance for MIMO cases.

Wireless sensor networks (WSNs) are gaining popularity in different areas of applications like industrial monitoring, military applications, home automation, smart grid applications, body organ monitoring, etc. A WSN is a wireless network comprising of a number of devices, called sensor nodes. A sensor node, usually battery powered, is capable of detecting physical phenomena, such as light, temperature, movement, noise, pressure, humidity, etc. Medium access control (MAC) protocols are in a key role for determining the energy efficiency of a WSN, which is a key design issue for battery operated sensor nodes. Alongside energy efficiency, reliable transmission is also always preferred in communication networks. The IEEE 802.15.4 standard provides low power solutions to the WSN applications by specifying physical and MAC layer functions for low rate wireless personal area networks. In this thesis, Markov chain models are derived to study the throughput and the energy consumption of IEEE 802.15.4 MAC taking into account the packet corruption by both collisions and channel errors. An increase in reliability reduces retransmissions of erroneous packets, which in turn reduces the energy consumption. Therefore, a network with low energy consumption and high reliability is always desired. Wireless radio channel is the medium used for the transmissions in WSNs and it is error prone leading to received data corruption. To mitigate this influence of channel to some extent, forward error correction (FEC) may be employed. FEC provides error correction with the addition of redundant bits to the original message. Various FEC codes are analysed to study the influence of coding on the performance of the IEEE 802.15.4 type networks. Along with the FEC, influence of data frame payload size on performance is also studied. Numerical analyses are carried out and illustrated using Matlab. The results show that the performance of an IEEE 802.15.4 type network can be improved using an appropriate choice of payload size and FEC.

Coordinated Multipoint (CoMP) transmission has been identified as a promising concept to handle the substantial interference in the LTE-Advanced systems and it is one of the key technology components in the future 5G networks. CoMP transmission involves two coordination schemes: joint processing (JP) and coordinated beamforming (CB). The scope of this thesis is limited to JP. In the CoMP JP scheme, each user is coherently served by multiple base stations (BSs) and consequently, the user’s signal strength is enhanced and the interference is mitigated. The coherent joint processing requires sharing data and channel state information (CSI) of all the users among all the BSs, which leads to high backhaul capacity requirement and high signaling cost especially in large-scale networks. Grouping the BSs into smaller coordination clusters within which a user is served by only the BSs in the cluster will significantly reduce the signaling cost and the backhaul burden. In this thesis, optimal BS clustering and beamformer design for CoMP JP in the downlink of a multi-cell network is studied. The unique aspect of the study is that the BS clustering and the beamformer design are carried out jointly by iteratively solving a series of convex sub-problems. The BSs are dynamically grouped into small coordination clusters whereby each user is served by a few BSs that are in a coordination cluster. The joint BS clustering and beamformer design is performed to maximize a network utility function in the form of the weighted sum rate maximization (WSRM). The weighted sum rate maximization (WSRM) problem is formulated from the perspective of sparse optimization framework where sparsity is induced by penalizing the objective function with a power penalty. The WSRM problem is known to be non-convex and NP-hard. Therefore, it is difficult to solve directly. Two solutions are studied; in the first approach, the WSRM problem is solved via weighted minimum mean square error (WMMSE) minimization and the second approach involves approximation of the WSRM problem as a successive second order cone program (SSOCP). In both approaches, the objective function is penalized with a power penalty and the clusters can be adjusted by a single parameter in the problem. The performance evaluation of the proposed algorithms is carried out via simulation and it is shown that the serving sets in the network can be controlled according to the available backhaul capacity by properly selecting a single parameter in the problem. Finally, an algorithm for a fixed number of active links is proposed.

Human Body Communication (HBC) is a novel communication method between devices which use human body as a transmission medium. This idea is mostly based on the concept of wireless biomedical monitoring system. The on-body sensor nodes can monitor vital signs of a human body and use the body as a transmission medium. This technology is convenient for long durations of clinical monitoring with the option of more mobility and freedom for the user. In this thesis, IEEE 802.15.6-2012 physical (PHY) layer for the HBC was simulated. Simulation model is following the standard’s requirements and processes. The human body was taken as a transmission medium and simulations, which follow the HBC standard, have been carried out. For the purpose of simulations, MATLAB is used as a platform to test and run the simulations. The constants and variables used in the simulations are taken from the IEEE 802.15 working group for wireless personal area networks (WPANs). The transmitter model and the receiver model have been taken from the standard, with changes done in it for performing the simulations on the PHY layer only. The simulations were done keeping in mind the dielectric properties of the outer layer of a human body, i.e., the dielectric values for human skin are noted and their corresponding values were used in the mathematical calculations. The work done here presents a transmitter and receiver architecture for the human body communication. The minimum data rate being 164 kbps and the transmitter being designed around the 21 MHz center frequency has achieved some outputs which are worth looking. The channel models used in this simulator are HBC channel and AWGN (additive white Gaussian noise) channel. It was observed that when signal was passed through AWGN channel, noise was added uniformly over the signal, while in the HBC channel signal strength is directly proportional to the transceiver ground sizes. In conclusion, the size of the ground terminals plays a critical role for the signal quality in the HBC simulator. The results in this thesis show that pathloss has certain linearity with the distance. The pathloss is calculated for different parts of the body with higher loss for structure with higher amount of bone, and vice versa. It is observed that in the HBC channel there are four factors with high impact on the system. These are the distances between the transceiver in air and on body while the other two are the sizes of the transceiver grounds. The size of the transmitter ground has been deemed very significant for the HBC from the simulations results. The four factors show high impact on the HBC channel. The signal strength is highly effected with the change in these four characteristics. From the simulation results it is evident that the HBC channel show a 15 to 20 dB deviation when compared to AWGN channel. The Eb⁄N0 for BER level at 10^(-3) for AWGN channel is 10 to 11 dB while for HBC it is around 27 dB showing a significant difference in the results.

In wireless communication systems, there is a need to design efficient schemes in order to overcome the problem of spectrum scarcity. One technology to address the problem of spectrum scarcity is cognitive radio (CR), in which a network entity is able to adapt intelligently to the environment through observation, exploration and learning. When multiple autonomous cognitive radios are searching for spectrum opportunities, they face competition from each other in order to access the available free channel. This will result in reduced throughput which occurs due to collision between cognitive radios, when they try to transmit in the same channel. The purpose of this thesis is to study a smart adaptation scheme for efficient channel access which enable autonomous cognitive radios to improve their overall bandwidth efficiency in a distributed cognitive radio network with the help of spatial reuse. An adaptive persistent strategy with efficient collision detection has been studied in this work for autonomous channel sensing order selection which enable distributed CRs to avoid collision and allow them to improve their overall system efficiency by increasing the average number of successful transmissions, especially, when number of available channels are less than the number of CRs competing to access these free channels. The performance of the studied strategy is compared with random selection of sensing orders. Simulation results are presented, which indicate that the studied strategy with spatial reuse achieves the highest number of successful transmissions in a given time slot as compared to other strategies. Simulation results are also compared for the case with no spatial reuse and the results indicate that it degrades the system efficiency by reducing the average number of successful transmissions in a given time slot.