The rapid growth of data hungry wireless applications has boosted the demand for wireless communication systems with improved reliability, wider coverage, and higher throughput. The main challenges facing the design of such systems are the limited resources, such as bandwidth, restricted transmission power, etc., and the impairments of the wireless channels, including fading effects, interference, and noise. Multiple-input multiple-output (MIMO) communication has been shown to be one of the most promising emerging wireless technologies that can efficiently enhance link reliability, improve system coverage, and boost the data transmission rate. Consequently, MIMO is now extensively adopted by many mainstream wireless industry standards, including 3GPP WCDMA/HSDPA, LTE, EVDO, WiFi, and WiMAX. By deploying multiple antennas at both transmitter and receiver sides, MIMO techniques license a new dimension (spatial dimension) that can be applied in various ways for combating the impairments of wireless networks. Furthermore, this new dimension has introduced a new concept known as Interference Alignment that can efficiently deal with the interference presentin the wireless communication networks. In particular, IA is highly attractive in terms of providing more degrees of freedom compared to techniques such as TDMA/FDMA. With this in mind, this thesis will focus on studying and developing advanced techniques and algorithms for reducing interference in cellular communication networks. The contributions of the thesis are as follows. Initially, a review is provided to reiterate some basic concepts of wireless communications and discuss the challenges faced by the techniques that deal with interference mitigation. Next, Chapter 3 presents a novel IA based cancellation scheme that is proposed for combating the interfering signals present in the compounded MIMO broadcast channels, where the users experience a multi-source transmission from several base stations. After defining the interference channel (IC) interference and X-channel interference, the partial transmit beamforming matrices of the closed-form downlink scheme alleviate the corresponding types of interference. Applying the proposed scheme allows one to treat the multi-cell network as a set of single-cell MIMO network, which leads to the simultaneous BER performance enhancement and data rate increase. Moreover, a generalization scheme is given to assign the appropriate antenna configuration for achieving maximum DoF. Furthermore, Chapter 4 demonstrates a comprehensive analysis on the number of DoF achievable by exploiting the transmit beamforming technique. Additionally, the proposed scheme is able to provide the maximum data rate under a certain antenna setting or compute a transmitter-receiver configuration in order to meet the required number of DoF. Chapter 5 considers a modified IA scheme for the compounded MIMO network when different classes of users communicate in the overlapped area. Due to various antenna settings of each receiver, the effect of spatial correlation on the achievable data rate is investigated. Moreover, an algorithm is derived for calculating the antenna configuration for different users classes. Then, the proposed scheme is extended for the case of Large-scale MIMO, which in turn provides sufficient insights into the impact of the deployment of a large number of antennas. Finally, Chapter 6 presents an alternative design of the IA scheme with no symbol extension for the cellular MIMO network. Subsequently, a modified eigenvalue-based scheme is proposed to enhance the overall system performance. Finally, the achievable data rate is calculated under different CSI acquisition scenarios. Chapter 7 concludes the thesis and provides a list of potential future work directions for further investigation.

Interference alignment (IA) has been shown to provide all users of an interference channel with half the capacity achievable in an interference free point-to-point link resulting in linear sum capacity scaling with the number of users in the high SNR regime. The linear scaling is achieved by precoding transmitted signals to align interference subspaces at the receivers, given channel knowledge of all transmit-receive pairs, effectively reducing the number of discernible interferers. The theory of IA was derived under assumptions about the richness of the propagation channel; practical channels do not guarantee such ideal characteristics. This paper presents the first experimental study of IA in measured multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels. We show that IA achieves the claimed scaling factors in a wide variety of measured channel settings for a 3 user, 2 antennas per node setup. In addition to verifying the claimed performance, we characterize the effect of several realistic system imperfections such as channel estimation error, feedback delay, and channel spatial correlation, on sum rate performance. / text

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR's) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA's ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR's ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input-multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU's unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU's receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates.

" In telecommunications, a cooperative scheme refers to a method where two or more users share or combine their information in order to increase diversity gain or power gain. In contrast to conventional point-to-point communications, cooperative communications allow different users in a wireless network to share resources so that instead of maximizing the performance of its own link, each user collaborates with its neighbours to achieve an overall improvement in performance. In this dissertation, we consider different models for transmission and reception and explore cooperative techniques that increase the reliability and capacity gains in wireless networks, with consideration to practical issues such as channel estimation errors and backhaul constraints. This dissertation considers the design and performance of cooperative communication techniques. Particularly, the first part of this dissertation focuses on the performance comparison between interference alignment and opportunistic transmission for a 3-user single-input single- output (SISO) interference channel in terms of average sum rate in the presence of channel estimation errors. In the case of interference alignment, channel estimation errors cause interference leakage which consequently results in a loss of achievable rate. In the case of opportunistic transmission, channel estimation errors result in a non-zero probability of incorrectly choosing the node with the best channel. The effect of these impairments is quantified in terms of the achievable average sum rate of these transmission techniques. Analysis and numerical examples show that SISO interference alignment can achieve better average sum rate with good channel estimates and at high SNR whereas opportunistic transmission provides better performance at low SNR and/or when the channel estimates are poor. We next considers the problem of jointly decoding binary phase shift keyed (BPSK) messages from a single distant transmitter to a cooperative receive cluster connected by a local area network (LAN). An approximate distributed receive beamforming algorithm is proposed based on the exchange of coarsely- quantized observations among some or all of the nodes in the receive cluster. By taking into account the differences in channel quality across the receive cluster, the quantized information from other nodes in the receive cluster can be appropriately combined with locally unquantized information to form an approximation of the ideal receive beamformer decision statistic. The LAN throughput requirements of this technique are derived as a function of the number of participating nodes in the receive cluster, the forward link code rate, and the quantization parameters. Using information-theoretic analysis and simulations of an LDPC coded system in fading channels, numerical results show that the performance penalty (in terms of outage probability and block error rate) due to coarse quantization is small in the low SNR regimes enabled by cooperative distributed reception. An upper/lower bound approximation is derived based on a circle approximation in the channel magnitude domain which provides a pretty fast way to compute the outage probability performance for a system with arbitrary number of receivers at a given SNR. In the final part of this dissertation, we discuss the distributed reception technique with higher- order modulation schemes in the forward link. The extension from BPSK to QPSK is straightforward and is studied in the second part of this dissertation. The extension to 8PSK, 4PAM and 16QAM forward links, however, is not trivial. For 8PSK, two techniques are proposed: pseudobeamforming and 3-bit belief combining where the first one is intuitive and turns out to be suboptimal,the latter is optimal in terms of outage probability performance. The idea of belief combining can be applied to the 4PAM and 16QAM and it is shown that better/finer quantizer design can further improve the block error rate performance. Information-theoretic analysis and numerical results are provided to show that significant reliability and SNR gains can be achieved by using the proposed schemes. "

Resource management in wireless networks is one of the key factors in maximizing the overall throughput. Contrary to popular belief, dividing the resources in a dense network does not yield the best results. A method that has been developed recently shares the spectrum amongst all the users in such a way that each node can potentially utilize about half of all the available resources. This new technique is often referred to as Interference Alignment and excels based on the fact that the amount of the network resources assigned to a user does not go to zero as the number of users in the network increases. Unfortunately it is still very difficult to implement the interference alignment concepts in practice. This thesis investigates some of the low-complexity solutions to integrate interference alignment ideas into the existing wireless networks. In the third and fourth chapters of this thesis, it is shown that introducing relays to a quasi-static wireless network can be very beneficial in terms of achieving higher degrees of freedom. The relays store the signals being communicated in the network and then send a linear combination of those signals. Using the proposed scheme, it is shown that although the relays cannot decode the original information, they can transform the equivalent channel in such a way that performing interference alignment becomes much easier. Investigating the required output power of the relays shows that it can scale either slower or faster than the output power of the main transmitters. This opens new doors for the applications that have constraints on the accessible output powers in the network nodes. The results are valid for both $X$ Channel and Interference Channel network topologies. In Chapter Five, the similarities between full-duplex transmitters and relays are examined. The results suggest that the transmitters can play the relay roles for offering easier interference alignment. Similar to the relay-based alignment, in the presented scheme full-duplex transmitters listen to the signals from other transmitters and use this information during the subsequent transmission periods. Studying the functionality of the full-duplex transmitters from the receivers' side shows the benefits of having a minimal cooperation between transmitters without even being able to decode the signals. It is also proved that the degrees of freedom for the $N$-user Interference Channel with full-duplex transmitters can be $\sqrt{\frac{N}{2}}$. The results offer an easy way to recover a portion of degrees of freedom with manageable complexity suited for practical systems.

This paper considers the combination of interference alignment and distributed antenna systems to improve the rate performance of cell-edge users in the cellular downlink. Because the power resources of each antenna in distributed antenna systems are geographically separated, practical implementations of distributed antenna systems require consideration of per-antenna power constraints on the transmit antennas. For this reason, we consider interference alignment with two types of power constraints: per-antenna power inequality constraints and per-antenna power equality constraints. On one hand, we show that interference alignment with per-antenna power inequality constraints is arbitrarily feasible using a technique of antenna power back-off but suffers from a loss of performance that we quantify in the case of Rayleigh-fading. On the other hand, we show that interference alignment with per-antenna power equality constraints does not suffer from a systematic loss of performance but yet requires more antennas to be feasible. We develop algorithms for implementing interference alignment with both types of constraints and numerically validate the results of our analysis. Finally, we demonstrate using the 3rd Generation Partnership Project spatial channel model in a cellular setting that interference alignment with distributed antenna systems has better rate performance than interference alignment with centralized antenna systems throughout the entire cell, especially near the cell boundary. / text

Wireless cellular networks, which serve a large area by geographically partitioning users, suffer from interference from adjacent cells transmitting in the same frequency band. This interference can theoretically be completely mitigated via transceiver cooperation in both the uplink and downlink. Optimally, base stations serving the users can utilize high-capacity backbones. to jointly transmit and receive all the data in the network across all the base stations. In reality, the backbone connecting the base stations is of finite capacity, limiting joint processing to localized clusters. Even with joint processing on a small scale, the overhead involved in sharing data between multiple base stations is large and time-sensitive. Other forms of cooperation have been shown to require less overhead while exhibiting much of the performance benefit from interference mitigation. One particular strategy, called interference alignment (IA), has been shown to exploit all the spatial degrees of freedom in the channel provided data cannot be shared among base stations. Interference alignment was developed for the multi-user interference channel to exploit independent channel observations when all of the links in the network have high signal-to-noise ratio, and assumes all the nodes utilizing the physical resources are participating in the cooperative protocol. When some or all of the links are at moderate signal-to-noise ratio, or when there are non-cooperating users, IA is suboptimal. In this dissertation, I take three approaches to addressing the drawbacks of IA. First, I develop cooperative transmission strategies that outperform IA in various operationg regimes, including at low-to-moderate SNR and in the presence of non-cooperating users. These strategies have the same complexity and overhead as IA. I then develop algorithms for network partitioning by directly considering the overhead of cooperative strategies. Partitioning balances the capacity gains of cooperation with the overhead required to achieve them. Finally, I develop the shared relaying model, which is equivalent to the interference channel but with a single multi-antenna relay mediating communications between transceivers. The shared relay requires less overhead and cooperation than interference alignment but requires added infrastructure. It is shown to outperform conventional relaying strategies in cellular networks with a fixed number of total relay antennas. / text

Resource management in wireless networks is one of the key factors in maximizing the overall throughput. Contrary to popular belief, dividing the resources in a dense network does not yield the best results. A method that has been developed recently shares the spectrum amongst all the users in such a way that each node can potentially utilize about half of all the available resources. This new technique is often referred to as Interference Alignment and excels based on the fact that the amount of the network resources assigned to a user does not go to zero as the number of users in the network increases. Unfortunately it is still very difficult to implement the interference alignment concepts in practice. This thesis investigates some of the low-complexity solutions to integrate interference alignment ideas into the existing wireless networks. In the third and fourth chapters of this thesis, it is shown that introducing relays to a quasi-static wireless network can be very beneficial in terms of achieving higher degrees of freedom. The relays store the signals being communicated in the network and then send a linear combination of those signals. Using the proposed scheme, it is shown that although the relays cannot decode the original information, they can transform the equivalent channel in such a way that performing interference alignment becomes much easier. Investigating the required output power of the relays shows that it can scale either slower or faster than the output power of the main transmitters. This opens new doors for the applications that have constraints on the accessible output powers in the network nodes. The results are valid for both $X$ Channel and Interference Channel network topologies. In Chapter Five, the similarities between full-duplex transmitters and relays are examined. The results suggest that the transmitters can play the relay roles for offering easier interference alignment. Similar to the relay-based alignment, in the presented scheme full-duplex transmitters listen to the signals from other transmitters and use this information during the subsequent transmission periods. Studying the functionality of the full-duplex transmitters from the receivers' side shows the benefits of having a minimal cooperation between transmitters without even being able to decode the signals. It is also proved that the degrees of freedom for the $N$-user Interference Channel with full-duplex transmitters can be $\sqrt{\frac{N}{2}}$. The results offer an easy way to recover a portion of degrees of freedom with manageable complexity suited for practical systems.

Wireless communication systems utilize the wireless medium to perform over-the-air (OTA) data transfer. There are many factors that can impact the quality of wireless communications, such as medium imperfection, interfering environment, mismatch of transceivers, etc. To mitigate these problems and improve the quality of service (QoS), this research study is conducted on three important topics including synchronization techniques, impairment estimation theory and techniques, and interference alignment techniques. In this thesis, it firstly present a dual link algorithm to align and manage the interference of multiple-input and multiple-output (MIMO) networks. A field-programmable gate array (FPGA) prototype is designed for software defined radio (SDR) platforms. As one of the key components, a hardware efficient architecture is proposed for the implementation of singular value decomposition (SVD). Secondly, it proposes a maximum-likelihood (ML) based synchronization approach for carrier frequency synchronization for MIMO systems. The algorithm is also implemented on FPGA for real-time performance evaluation. Finally, as an exemplary study of machine learning techniques for wireless communications, a neural network (NN) based estimator is proposed to perform coarse frequency offset estimations for MIMO systems. The proposed NN based estimator can accommodate various channel models and the results show promising performance in terms of accuracy and estimation range. In summary, this thesis provides a comprehensive study on interference alignment, carrier synchronization, and impairment estimation using different approaches. Efficient hardware implementations for the key algorithms are also presented.

Wireless communication systems utilize the wireless medium to perform over-the-air (OTA) data transfer. There are many factors that can impact the quality of wireless communications, such as medium imperfection, interfering environment, mismatch of transceivers, etc. To mitigate these problems and improve the quality of service (QoS), this research study is conducted on three important topics including synchronization techniques, impairment estimation theory and techniques, and interference alignment techniques. In this thesis, it firstly present a dual link algorithm to align and manage the interference of multiple-input and multiple-output (MIMO) networks. A field-programmable gate array (FPGA) prototype is designed for software defined radio (SDR) platforms. As one of the key components, a hardware efficient architecture is proposed for the implementation of singular value decomposition (SVD). Secondly, it proposes a maximum-likelihood (ML) based synchronization approach for carrier frequency synchronization for MIMO systems. The algorithm is also implemented on FPGA for real-time performance evaluation. Finally, as an exemplary study of machine learning techniques for wireless communications, a neural network (NN) based estimator is proposed to perform coarse frequency offset estimations for MIMO systems. The proposed NN based estimator can accommodate various channel models and the results show promising performance in terms of accuracy and estimation range. In summary, this thesis provides a comprehensive study on interference alignment, carrier synchronization, and impairment estimation using different approaches. Efficient hardware implementations for the key algorithms are also presented.