The benefits of MIMO technology have made it a solution for the present and future wireless networking demands. Increasing the number of antennas is an intuitive approach for boosting the network capacity; however, processing load and implementation limitations put a practical bound on this goal. Recently a solution known as massive MIMO has shown that a very large antenna array at the base station can simplify the processing, in a way that even matched filter (MF) can be used for detection purpose. The ultimate performance of massive MIMO can be achieved only under some optimistic assumptions about the channel and hardware deployment. In practice, there are some restrictions that do not allow the ultimate performance for a massive MIMO system. Under some realistic assumptions, an efficient use of all the resources becomes important in a way that the application of simple algorithms like MF and zero forcing (ZF) becomes questionable. Thus, in this thesis work, more efficient approach based on optimal minimum power beamforming is considered as the benchmark. The idea is to investigate the behavior of this algorithm and the performance differences with respect to some sub-optimal methods when the system dimensions grow large. Two solutions for the minimum power beamforming are reviewed (SOCP and uplink-downlink duality). The solution that is on focus is based on the second order cone programming (SOCP). Intercell interference(ICI) plays a critical role in the SOCP algorithm as it couples the sub-problems at the base stations. Thus, a large dimension approximation for the optimal ICI, using random matrix theory tools, is derived which tackles both of the processing simplification and the backhaul exchange rate reduction goals. This approximation allows derivation of an approximated optimal intercell interference based on the channel statistics that results a procedure for decoupling the subproblems at base stations. The comparison between the SOCP algorithm and the sub-optimal methods is carried out via simulation. The results show that the performance gap with respect to the sub-optimal methods grows when correlation between the antenna elements at the BS side increase. In a network simulation with 7 cell and 28 users, this gap remains significant even with 100 antennas at the BS side. These performance differences justify the application of more complex algorithms like SOCP for a MIMO system with a large antenna array when the practical restrictions are taken into account.

The future demand of increased transmission rate and bandwidth efficiency is of prime concern in the modern wireless communication systems. Faster than Nyquist signaling (FTN) is under the great interest of research to address this issue of high data rate, which is also a major requirement, for the fifth generation (5G) communication networks. The data bits are transmitted at a rate higher than the conventional methods which are bounded by the Nyquist condition and the outputs are compared so as to analyze the benefits. Receiver processing techniques are implemented to achieve the high data rate with improved error performance at the lower decoding complexity. Considering the bandwidth efficiency as a key factor, more data symbols are sent at the given time interval by reducing the time period for signal transmission. This ensures more data being transmitted. In the scenario of perfect Nyquist signaling, pulse designs were based on the principle of orthogonality. The signal pulse form h(t) is orthogonal with respect to shifts by nT, where T is the signaling interval. In the thesis, the time period is reduced to T < 1, which prompt more symbols to be transmitted. The pulses are no longer orthogonal. These non orthogonal FTN signals are accepted as a promising approach for the required solution of increased data rate. FTN comes as a tradeoff between the high data rate achievement and error probability. Reduction of the time factor affirms good data rate but at the same time, cost of high error rate has to be paid. Efficient receiver processing techniques are designed to compensate between these two factors. Main obstacle due to the reduction of time period in FTN signaling is to tackle the unavoidable inter symbol interferences (ISI). Going beyond the Nyquist bound, as a consequence, results high ISI. This necessitates an effective receiver processing to overcome the ISI. Minimum mean square error (MMSE) detection algorithm is employed to equalize the received signals and analyze the performance of the FTN system. Finally, the system portrayal is studied by processing the results under the implementation of turbo coding systems. The bit error rate (BER) characteristics are analyzed under these circumstances. Efficient encoding pattern and decoding algorithm helps in reducing the errors. Analysis of the simulation results show that the turbo code proficiency is improved by increasing the number of iterations. Performance indication is also related to the frame size or the interleaver size and the signal power. In other words, it comes as a trade-off between energy efficiency, bandwidth efficiency, complexity and error rates. Furthermore, for the fair comparison of the performance analysis, transmission rates for turbo coded transmission systems under the conditions of Nyquist signaling and FTN signaling are made equivalent.

A wireless body area network (WBAN) is a collection of miniaturized and energy efficient wireless sensor nodes which monitor human body functions and its surroundings. It has been observed that WBANs perform single application per network, computation and storage capacities are scarce and there is no or limited mobility support. Technically complex WBAN application solutions today, find refuge in processing computationally complex data external to WBANs, i.e., processing sensor data on a conventional PC which is impractical and clumsy. There is a strong need for WBAN platforms which can perform computationally complex tasks on their own having enough resources in terms of computation and memory but still consuming as low power as possible in order to prolong network uptime. In this thesis work, an improved WBAN named multipurpose-BodyNet (MPBodyNet) is implemented. It has enough computational and memory resources and compact software solutions to achieve high performance and fidelity. MPBodyNet is a self-configuring, multipurpose WBAN which can perform multiple applications and user can switch between applications by a mere push of button. It supports mobility and it acts like an agent network to other networks. MP-BodyNet forms a hierarchy where low-capability networks are supported by higher-capacity networks. Hardware used for MP-BodyNet has been designed by WSN-Team at Centre for Wireless Communications, University of Oulu and this thesis proposes two application scenarios. Senior citizen protection mode (SPM) deals with a very hot health care issue for elderly people and patients. An algorithm is proposed and implemented that can detect falls or if the subject/patient has fainted. In SPM, MP-BodyNet can generate alarms in case of emergency and events can be seen on a central server as well as a special alarm is generated to the user’s phone (android app.) which can in turn establish an emergency call automatically. Algorithmic efficiency achieved is 100%. Silent communication mode (SCM) deals with a military hand signal/gesture recognition application. A quite complex pattern recognition algorithm has been proposed with two novelties in it i.e., a sampling process is introduced in the algorithm and the whole algorithmic processing is supposed to be done on the sensor node itself, no processing is supposed to be happening external to the WBAN. Algorithm for SCM is only presented here conceptually after rigorous research about the subject at disposal. It is not implemented in this thesis due to lack of time and is saved for future development. After a gesture would be recognized, an audio message mapped to the gesture will be heard over a headphone.

Full duplex (FD) radios are the next generation wireless paradigm to answer the growing demand of high capacity along with energy and spectrum efficient wireless transceivers. Given the colossal power difference between the transmit and receive signal, self-interference cancellation becomes one of the key challenge in the design of a FD radio. A model of self-interference channel is required to develop a robust cancellation mechanism. One of the key contribution of this thesis is to define the properties of the self-interference channel. Furthermore, an analog baseband cancellation mechanism for FD transceivers is also defined, which can be used as a cancellation stage before the signal goes to digital domain. The self-interference channel was measured using ultra wide-band antennas (UWB). Narrow-band measurement technique i.e., a vector network analyzer (VNA) was used for the channel measurements. Spatial resolution of 4.3 cm was achieved. Measurements were done in variety of locations including an anechoic chamber with different antenna orientation. Antennas were mounted on an old laptop frame. Coherence bandwidth of the self-interference channel was found to be varying between 1 MHz and 10 MHz, effectively making it a frequency selective channel. The average amount of isolation was found to be around 40 dB irrespective of the antennas relative orientation. It was also observed that a major amount of power was transferred because of direct coupling between the antennas and this coupling was due of the frame on which antennas were mounted. Using the defined analog baseband cancellation mechanism, an orthogonal frequency division multiplexing (OFDM) based transceiver was simulated using Matlab. The impact of different bit analog-to-digital converter (ADC), digital-to-analog converter (DAC), different training sequence length for the desired and the self-interference channel, were observed in the simulations. The simulations were performed for both 16 and 64 quadrature amplitude modulation (QAM). Training symbols were used in front of the data frame to estimate both the desired and self-interference channel and also to set the gain of variable gain amplifiers (VGA). The least square algorithm was used for the estimates. The self-interference power was set to −20 dBm and thermal noise floor was set to −81.68 dBm. It was found that a twelve bit ADC along with a sixteen bit DAC would provide a performance within 1.5 dB of theoretical performance.

Nowadays, wireless device users engage in various forms of wireless applications and services. Multiple-Input Multiple-Output (MIMO) system technology, which involves multiple uses of antennas at both the transmitter and the receiver side of wireless channel, can be used to improve the wireless channel capacity without any need for extra spectrum in the rich scattering environment. The MIMO technology is regarded as a fundamental component for this new emerging wireless communication Long Term Evolution (LTE) standard. However, as a result of short distance between the antennas in the small mobile terminals, the total antenna efficiency gets reduced and the mutual coupling that exists between the MIMO antenna elements also becomes very high which lead to high Envelope Correlation Coefficient (ECC). This Master’s thesis aims to study the impact of antenna type on the ECC for a two antenna system in a typical mobile terminal sized device (ground plane) by using different configurations of antenna placement. The mobile antennas are to operate in LTE band 3 (from 1.710 GHz to 1.880 GHz) and LTE band 20 (from 0.791GHz to GHz 0.862 GHz). This thesis has been addressed by first introducing the fundamental theory of antennas. It is followed with description of effect on ground plane due to different mobile antenna structures and as a last part on the basics of LTE and LTE-Advanced components, focusing on the concept of multiple antennas design on mobile terminal. In this thesis, three types of antenna structures have been considered: Planar Inverted-F Antenna (PIFA), monopole and loop antennas. The designs and simulations of the antenna structures have been performed using CST Microwave studio software. The two antenna systems showed better performance when one antenna is located at the bottom of the ground plane with feed at the corner and the second antenna is placed perpendicularly at the top with feed positioned on the same side of the ground plane as the bottom antenna. ECC values of less than 0.2 in LTE band 3 and less than 0.49 in LTE band 20 were obtained. The study shows that good efficiency and low ECC (low mutual coupling) can be achieved from the placement of the MIMO antennas on the ground plane. In consideration to future work, the results in this thesis can serve as helpful information in multi-antenna designs for mobile terminals.

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.