This dissertation focuses on the development of next generation wireless communications at millimeter-wave and sub-terahertz frequencies. As wireless providers experience a bandwidth shortage and cellular subscribers demand faster data rates and more reliable service, a push towards unused carriers fre- quencies such as 28 GHz, 60 GHz, and 180 GHz will alleviate network conges- tion while simultaneously providing massive bandwidths to consumers. This dissertation summarizes research in understanding millimeter-wave wireless propagation, the design and fabrication of millimeter-wave and sub-terahertz on-chip antenna arrays on an integrated circuit semiconductor process, and the accurate measurement of on-chip antenna radiation patterns in a wafer probe station environment. / text

The radio spectrum is becoming increasingly congested everyday with emerging technologies and with the increasing number of wireless devices. Considering the limited bandwidth availability, accommodating the demand for higher capacity and data rates is a challenging task, requiring innovative technologies that can offer new ways of exploiting the available radio spectrum. Cognitive radio arises to be a tempting solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Because of its attractive features, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. We believe that OFDM will play an important role in realizing the cognitive radio concept as well by providing a proven, scalable, and adaptive technology for air interface. The goal of this dissertation is to identify and address some of the challenges that arise from the introduction of cognitive radio. Specifically, we propose methods for obtaining awareness about channel, spectrum, and waveform in OFDM-based cognitive radio systems in this dissertation. Parameter estimation for enabling adaptation, spectrum sensing, and OFDM system identification are the three main topics discussed. OFDM technique is investigated as a candidate for cognitive radio systems. Cognitive radio features and requirements are discussed in detail, and OFDM's ability to satisfy these requirements is explained. In addition, we identify the challenges that arise from employing OFDM technology in cognitive radio. Algorithms for estimating various channel related parameters are presented. These parameters are vital for enabling adaptive system design, which is a key requirement for cognitive radio. We develop methods for estimating root-mean-square (RMS) delay spread, Doppler spread, and noise variance. The spectrum opportunity and spectrum sensing concepts are re-evaluated by considering different dimensions of the spectrum which is known as multi-dimensional spectrum space. Spectrum sensing problem in a multi-dimensional space is addressed by developing a new sensing algorithm termed as partial match filtering (PMF). Cognitive radios are expected to recognize different wireless networks and have capability of communicating with them. Algorithms for identification of multi-carrier transmissions are developed. Within the same work, methods for blindly detecting transmission parameters of an OFDM based system are developed. Blind detection is also very helpful in reducing system signaling overhead in the case of adaptive transmission where transmission parameters are changed depending on the environmental characteristics or spectrum availability.

Link adaptation is an important component of contemporary wireless networks that require high spectral efficiency and service a variety of network applications/configurations. By exploiting information about the wireless channel, link adaptation strategically selects wireless communication transmission parameters in real-time to optimize performance. Link adaptation in practice has proven challenging due to impairments outside system models and analytical intractability in modern broadband networks with multiple antennas (MIMO), orthogonal frequency division multiplexing (OFDM), forward error correction, and bit-interleaving. The objective of this dissertation is to provide simple and flexible link adaptation algorithms with few link model assumptions that are amenable to modern wireless networks. First, a complete design and analysis of supervised learning for link adaptation in MIMO-OFDM is provided. This includes the construction of a publicly available data set, a new frame error rate bound leading to a new feature set, and IEEE 802.11n performance evaluation to verify that my design outperforms existing link quality metrics. Next, two supervised learning classification algorithms are designed to exploit information collected from packets transmitted and received over standard links in real time: database learning with nearest neighbor classifiers and support vector machines. Algorithms are also proposed to preserve diversity of feature sets in the database and to allow learning algorithms to seek out more information about the network. Finally, link adaptation with supervised learning is applied to MIMO-OFDM systems where the modulation order may be adapted per-stream. This leads to the analysis of the ordered SNR per stream and its connection to the cumulative distribution function of SNR on each stream. Decoupled link adaptation algorithms, which significantly reduce the complexity of non-uniform link adaptation algorithms, are proposed. New analysis of non-uniform link adaptation shows that the performance of decoupled link adaptation algorithms converge to the performance of joint (optimal) link adaptation algorithms as the number of modulation and coding options per-stream increase. This guides the construction of future standards to reduce the complexity of link adaptation in MIMO-OFDM. / text

The research in wireless communications and in-vehicle computing systems has opened up new fields of applications for transportation systems. Vehicular ad hoc networks (VANETs) emerge as a contribution to the solution of providing safer and more efficient roads and to increase passenger safety. This thesis treats different issues that influence the performance of wireless vehicle communication systems and it proposes a general design procedure for the construction of a test environment for VANETs. A comprehensive survey of the different parameters that affect the system performance in the field of wireless vehicle communications is provided. These parameters are then analysed and quantified to serve as guidelines when identifying and designing the different components of the test environment. One such component is a simulator that enables VANET performance evaluation and allows identification of bottlenecks in the network functionality. In addition, suggestions for a hardware platform and an operating system for the development of a suitable on-board test-bed for performance measurements are presented. The design procedure of such a test environment is intended to be used by researchers and engineers working in the field of wireless communications and ad hoc networking with special regard to the automotive sector.

We present a new sub-optimal near-maximum-likelihood (ML) detection method for the family of variable-rate space-time block codes (VRSTBC). The proposed detection method is based on the concept of symbol reliability and provides a wide range of performance-complexity trade-offs. The reliability measures are defined with the help of a recent generic ML metric expression. The error performance and complexity analysis of the method via simulations show an achievable near-ML error performance with significant reduction in complexity. The performance of the proposed method is also compared with the group interference cancellation (GIC) method which was the detection method originally applied to VRSTBCs and the results show a significant improvement. The new method offers various levels of error protection via a simple parameter and hence can provide the users of a wireless network with different performance levels according to their cost allowance. Unequal error protection by VRSTBCs under the new detection method was explored. Several applications integrating data with different levels of sensitivity to error can benefit from the wide range of possibilities that the combination of the proposed detection method and VRSTBCs provides. To further explore these flexibilities, four practically interesting power allocation schemes were applied to the transmission and the behaviors were observed through case studies. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-09-26 23:45:07.81

The fifth generation (5G) wireless communications technology will be a paradigm shift which does not only provide an explosive increment on the achievable data rate per cell, but also ideally decreases the costs and energy consumption per data link. The engineering requirements of 5G standard can be intuitively interpreted as highly enhanced spectral efficiency and energy efficiency. This thesis focuses on the practical implementation issues of the massive multiple-input multiple-output (MIMO) and energy harvesting systems. To begin with, massive MIMO, as one of the key technologies of 5G systems, can provide enormous enhancement in spectral efficiency. For a practical massive MIMO system, hybrid processing (precoding/combining), by restricting the number of RF chains to far less than the number of antenna elements, can significantly reduce the implementation cost compared to the full-complexity radio frequency (RF) chain configuration. This thesis designs the hybrid RF and baseband precoders/combiners for multi-stream transmission in the point-to-point (P2P) massive MIMO systems, by directly decomposing the pre-designed digital precoder/combiner of a large dimension. The performance of the matrix decomposition based hybrid processing (MD-HP) scheme is near-optimal compared to the singular value decomposition (SVD) based full-complexity processing. In addition, the downlink communication of a massive multiuser MIMO (MU-MIMO) system is also investigated, and a low-complexity hybrid block diagonalization (Hy-BD) scheme is developed to approach the performance of the traditional BD method. We aim to harvest the large array gain through the phase-only RF precoding and combining and then BD processing is performed on the equivalent baseband channel in the massive MU-MIMO scenario. The MD-HP and Hy-BD schemes are examined in both the large Rayleigh fading channels and millimeter wave channels. On the other hand, energy harvesting is an increasingly attractive and renewable source of power for wireless communications devices, which contributes to the enhancement of the system energy efficiency. This thesis also designs the energy cooperation assisted energy harvesting communication between a practical transmitter and receiver, whose hardware circuits consume non-zero power when active. The energy cooperation save-then-transmit (EC-ST) scheme aims to obtain the optimal active time ratio and energy cooperation power for the maximum throughput under additive white Gaussian channels and the minimum outage probability under block Rayleigh fading channels. / Graduate

Multiple antennas at each side of the communication channel seem to be vital for future wireless communication systems. Multi-antenna communication provides throughput gains roughly proportional to the smallest number of antennas at the communicating terminals. On the other hand, multiple antennas at a terminal inevitably increase the hardware complexity of the latter. For efficient design of such systems relevant mathematical tools, capable of capturing the most significant features of the wireless multi-antenna channel - such as fading, spatial correlation, interference - are essential. This thesis, based on the asymptotic methods from statistical physics and random matrix theory, develops a series of asymptotic approximations for various metrics characterizing the performance of multi-antenna systems in different settings. The approximations become increasingly precise as the number of antennas at each terminal grows large and are shown to significantly simplify the performance analysis. This, in turn, enables efficient performance optimization, which would otherwise be intractable. After a general introduction, provided in Chapter 2, this thesis provides four different applications of large-system analysis. Thus, Chapter 3 analyzes multi-antenna multiple-access channel in the presence of non-Gaussian interference. The obtained large-system approximation of the sum rate is further used to carry out the precoder optimization routine for both Gaussian and finite-alphabet types of inputs. Meanwhile, Chapter 4 carries out the large-system analysis for a multi-hop relay channel with an arbitrary number of hops. Suboptimality of some conventional detectors has been captured through the concept of generalized posterior mean estimate. The obtained decoupling principle allows performance evaluation for a number of conventional detection schemes in terms of achievable rates and bit error rate. Chapter 5, in turn, studies achievable secrecy rates of multi-antenna wiretap channels in three different scenarios. In the quasi-static scenario, an alternating-optimization algorithm for the non-convex precoder optimization problem is proposed. The algorithm is shown to outperform the existing solutions, and it is conjectured to provide a secrecy capacity-achieving precoder. In the uncorrelated ergodic scenario, a large-system analysis is carried out for the ergodic secrecy capacity yielding a closed-form expression. In the correlated ergodic scenario, the obtained large-system approximation is used to address the corresponding problem of precoder optimization. Finally, Chapter6 addresses a practical case of random network topology for two scenarios: i) cellular mobile networks with randomly placed mobile users and ii) wiretap channel with randomly located eavesdroppers. Large-system approximations for the achievable sum rates are derived for each scenario, yielding simplified precoder optimization procedures for various system parameters. / <p>QC 20140901</p>

In this dissertation, we study cross-layer design for cooperative wireless data communication networks. Based on the characteristics of cooperative wireless communications, and the requirement of Quality of Service (QoS) provisioning for data networks, we consider cross-layer system design for cooperative wireless networking. Three major design issues which cover cooperative link establishment, information security of cooperative communications, and cross-layer cooperative transmission scheduling, are investigated. Specifically, we follow the communication procedure in cooperative wireless systems and investigate several cross-layer design problems. Considering the queueing behavior of data buffers at the candidate relays, we study relay selection from a queue-aware perspective which takes into account the queueing systems at both the source and the potential relays. With the cooperative link established, we then study the secret key establishment problem by cross-layer cooperative discussion. Then cross-layer transmission scheduling is investigated from two perspectives. We first look at cross-layer adaptive modulation and coding (AMC), which takes both the channel condition and traffic intensity into consideration in the scheduling design. A more general queue-aware scheduler state selection mechanism based on buffer queue occupancy is studied, and optimization by nonlinear integer programming is presented. / Graduate / 0544

This thesis deals with wireless channels in uncorrelated block fading environment with Rayleigh distribution. All nodes are assumed to be oblivious to their forward channel gains; however, they have perfect information about their backward channel gains. We also assume a stringent decoding delay constraint of one fading block that makes the definition of ergodic (Shannon) capacity meaningless. In this thesis, we focus on two different systems. In each case, the throughput and expected-rate are analyzed. First, the point-to-point multiple-antenna channel is investigated in chapter 2. We prove that in multiple-input single-output (MISO) channels, the optimum transmission strategy maximizing the throughput is to use all available antennas and perform equal power allocation with uncorrelated signals. Furthermore, to increase the expected-rate, multilayer coding (the broadcast approach) is applied. Analogously, we establish that sending uncorrelated signals and performing equal power allocation across all available antennas at each layer is optimum. A closed form expression for the maximum continuous-layer expected-rate of MISO channels is also obtained. Moreover, we investigate multiple-input multiple-output (MIMO) channels, and formulate the maximum throughput in the asymptotically low and high SNR regimes and also asymptotically large number of transmit or receive antennas by obtaining the optimum transmit covariance matrix. Furthermore, a distributed antenna system, wherein two single-antenna transmitters want to transmit a common message to a single-antenna receiver, is considered. It is shown that this system has the same outage probability and hence, throughput and expected-rate, as a point-to-point 2x1 MISO channel. In chapter 3, the problem of dual-hop transmission from a single-antenna source to a single-antenna destination via two parallel full-duplex single-antenna relays under the above assumptions is investigated. The focus of this chapter is on simple, efficient, and practical relaying schemes to increase the throughput and expected-rate at the destination. For this purpose, various combinations of relaying protocols and multi-layer coding are proposed. For the decode-forward (DF) relaying, the maximum finite-layer expected-rate as well as two upper-bounds on the continuous-layer expected-rate are obtained. The main feature of the proposed DF scheme is that the layers being decoded at both relays are added coherently at the destination although each relay has no information about the number of layers being successfully decoded by the other relay. It is proved that the optimum coding scheme is transmitting uncorrelated signals via the relays. Next, the maximum expected-rate of ON/OFF based amplify-forward (AF) relaying is analytically formulated. For further performance improvement, a hybrid decode-amplify-forward (DAF) relaying strategy, adopting multi-layer coding at the source and relays, is proposed and its maximum throughput and finite-layer expected-rate are presented. Moreover, the maximum throughput and expected-rate in the compress-forward (CF) relaying adopting multi-layer coding, using optimal quantizers and Wyner-Ziv compression at the relays, are fully derived. All theoretical results are illustrated by numerical simulations. As it turns out from the results, when the ratio of the relay power to the source power is high, the CF relaying outperforms DAF (and hence outperforms both DF and AF relaying); otherwise, DAF scheme is superior.

This dissertation examines multi-antenna transceiver design over flat-fading wireless channels. Bit Interleaved Coded Modulation (BICM) and MultiLevel Coded Modulation (MLCM) transmitter structures are considered, as well as the used of an optional spatial precoder under slow and quasi-static fading conditions. At the receiver, MultiStage Decoder (MSD) and Iterative Detection and Decoding (IDD) strategies are applied. Precoder, mapper and subcode designs are optimized for different receiver structures over the different antenna and fading scenarios. Under slow and quasi-static channel conditions, fade resistant multi-antenna transmission is achieved through a combination of linear spatial precoding and non-linear multi-dimensional mapping. A time-varying random unitary precoder is proposed, with significant performance gains over spatial interleaving. The fade resistant properties of multidimensional random mapping are also analyzed. For MLCM architectures, a group random labelling strategy is proposed for large antenna systems. The use of complexity constrained receivers in BICM and MLCM transmissions is explored. Two multi-antenna detectors are proposed based on a group detection strategy, whose complexity can be adjusted through the group size parameter. These detectors show performance gains over the the Minimum Mean Squared Error (MMSE)detector in spatially multiplexed systems having an excess number of transmitter antennas. A class of irregular convolutional codes is proposed for use in BICM transmissions. An irregular convolutional code is formed by encoding fractions of bits with different puncture patterns and mother codes of different memory. The code profile is designed with the aid of extrinsic information transfer charts, based on the channel and mapping function characteristics. In multi-antenna applications, these codes outperform convolutional turbo codes under independent and quasi-static fading conditions. For finite length transmissions, MLCM-MSD performance is affected by the mapping function. Labelling schemes such as set partitioning and multidimensional random labelling generate a large spread of subcode rates. A class of generalized Low Density Parity Check (LDPC) codes is proposed, to improve low-rate subcode performance. For MLCM-MSD transmissions, the proposed generalized LDPC codes outperform conventional LDPC code construction over a wide range of channels and design rates.