Position location in wireless MIMO communication systems

Motivation and objectives -- Contributions -- Organization of the thesis -- Wireless communication channels -- Overview of wireless position location systems -- Fundamentals of array signal processing -- Mimo and space-time processing -- Bidirectional mimo channel model -- The system model -- The bidirectional beamforming MIMO channel -- Joint estimation of multipath parameters for Mimo systenms -- The proposed maximum likelihood multipath parameter estimation algorithms -- The proposed subspace-based multipath parameter estimation algorithm -- The cramer-rao lower bound -- Position location of mobile terminal in mimo systems -- The proposed hybrid TDOA/AOA/AOD location method for Mimo systems -- Analysis of the proposed location method for MIMO systems

Ultra wideband antenna array processing under spatial aliasing

Given a certain transmission frequency, Shannon spatial sampling limit de¯nes an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). This spacing limit is inversely proportional to the frequency of transmis- sion. Therefore, to meet a wider spectral support, the element spacing should be decreased. However, practical implementations of closely spaced elements result in a detrimental increase in electromagnetic mutual couplings among the sensors. Further- more, decreasing the spacing reduces the array angle resolution. In this dissertation, the problem of Direction of Arrival (DOA) estimation of broadband sources is ad- dressed when the element spacing of a Uniform Array Antenna (ULA) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the frequency diversity of the broadband sources. An algorithm, based on Maximum Likelihood Estimator (MLE), is proposed to estimate the transmitted data signal and the DOA of each source. In the sequel, a subspace-based algorithm is developed and the prob- lem of order estimation is discussed. The adopted signaling framework assumes a subband hopping transmission in order to resolve the problem of source associations and system identi¯cation. The proposed algorithms relax the stringent maximum element-spacing constraint of the arrays pertinent to the upper-bound of frequency transmission and suggest that, under some mild constraints, the element spacing can be conveniently increased. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed algorithms. Through con- ¯rmatory simulation, it is shown that the performance gain of the proposed setup is potentially signi¯cant, speci¯cally when the transmitters are closely spaced and under low Signal to Noise Ratio (SNR), which makes it applicable to license-free communication

Doppler spread estimation in mobile fading channels

The Doppler spread, or equivalently, the mobile speed, is a measure of the spectral dispersion of a mobile fading channel. Accurate estimation of the mobile speed is important in wireless mobile applications which require such as knowledge of the rate of channel variations. In this dissertation, first the performance of classical crossing- and covariance-based speed estimators is studied. Next, the problem of mobile speed estimation using diversity combining is investigated. Then, a nonparametric estimation technique is proposed that is robust to different channel variations. Finally, cyclostationarity-based speed estimators which can be applied either blindly or with the aid of pilot data, are developed. A unified framework for the performance analysis of well-known crossing and covariance based speed estimation techniques is presented. This allows a fair analytical comparison among all the methods. Interestingly, it is proved that all these methods are asymptotically equivalent, i.e., for large observation intervals. The extensive performance analysis, supported by Monte Carlo simulations, has revealed that depending on the channel condition and the observation interval, one needs to use a crossing or a covariance based technique to achieve the desired estimation accuracy over a large range of mobile speeds. Two common diversity schemes, selection combining (SC) and maximal ratio combining (MRC), are considered for Doppler spread estimation. Four new estimators are derived which rely on the inphase zero crossing rate, inphase rate of maxima, phase zero crossing rate, and the instantaneous frequency zero crossing rate of the output of SC. Two estimators, which work based on the level crossing rates of the envelopes at the output of SC and MRC, are also proposed. The performances of all these estimators are investigated in realistic noisy environments with different kinds of scatterings and different numbers of diversity branches. Then a novel speed estimation technique is proposed that is applicable to both mobile and base stations, based on the characteristics in the power spectrum of mobile fading channels. The analytic performance analysis, verified by Monte Carlo simulations, shows that this low-complexity estimator is not only robust to both Gaussian and non-Gaussian noises, but also insensitive to nonisotropic scattering observed at the mobile. The estimator performs very well in both two- and three-dimensional propagation environments. By taking advantage of resolvable paths in wideband fading channels, the robustness against both nonisotropic scattering and line of sight can be further increased, due to the differences among the Doppler spectra observed at different paths. This technique is also extended to base stations with antenna arrays. By exploiting the spatial information, the proposed space-time estimator exhibits excellent performance over a wide range of noise power, nonisotropic scattering, and the line-of-sight component. This is all verified by simulation. The utility of the new method is further demonstrated by applying it to the measured data. Finally, to design robust blind and data-aided mobile speed estimators, a proposal is made to exploit the inherent cyclostationarity of linearly modulated signals transmitted through fading channels. Two categories of cyclic-correlation- and cyclic-spectrum-based methods are developed. Extension to space-time speed estimation at the base station in macrocells is also provided. In comparison with the existing methods, the new estimators can be used without any need for pilot tones and are robust to additive stationary noise or interference of any color or distribution. Unlike the conventional multi-antenna based method, the proposed space-time speed estimator does not assume the receiver noise to be spatially white. A suboptimal training sequence is also devised for pilot-symbol assisted methods, to reduce the estimation error. The performance of the proposed estimators are illustrated via extensive Monte Carlo simulations

Application of genetic algorithm to wireless communications

Wireless communication is one of the most active areas of technology development of our time. Like all engineering endeavours, the subject of the wireless communication also brings with it a whole host of complex design issues, concerning network design, signal detection, interference cancellation, and resource allocation, to name a few. Many of these problems have little knowledge of the solution space or have very large search space, which are known as non-deterministic polynomial (NP) -hard or - complete and therefore intractable to solution using analytical approaches. Consequently, varied heuristic methods attempts have been made to solve them ranging from simple deterministic algorithms to complicated random-search methods. Genetic alcyorithm (GA) is an adaptive heuristic search algorithm premised on the evolutionary ideas of evolution and natural selection, which has been successfully applied to a variety of complicated problems arising from physics, engineering, biology, economy or sociology. Due to its outstanding search strength and high designable components, GA has attracted great interests even in the wireless domain. This dissertation is devoted to the application of GA to solve various difficult problems spotlighted from the wireless systems. These problems have been mathematically formulated in the constrained optimisation context, and the main work has been focused on developing the problem-specific GA approaches, which incorporate many modifications to the traditional GA in order to obtain enhanced performance. Comparative results lead to the conclusion that the proposed GA approaches are generally able to obtain the optimal or near-optimal solutions to the considered optimisation problems provided that the appropriate representation, suitable fitness function, and problem-specific operators are utilised. As a whole, the present work is largely original and should be of great interest to the design of practical GA approaches to solve realistic problems in the wireless communications systems.EThOS - Electronic Theses Online ServiceBritish Council (ORS) : Newcastle UniversityGBUnited Kingdo

Physical layer network coding based communication systems in frequency selective channels

PhD ThesisThe demand for wireless communications is growing every day which requiresmore speed and bandwidth. In two way relay networks (TWRN), physical layer network coding (PLNC) was proposed to double the bandwidth. A TWRN is a system where two end users exchange data through a middle node called the relay. The two signals are allowed to be physically added before being broadcasted back to the end users. This system can work smoothly in flat fading channels, but can not be applied straightforward in frequency selective channels. In a multipath multi-tap FIR channel, the inter-symbol interference (ISI) spreads through several symbols. In this case, the symbols at the relay are not just an addition of the sent symbols but also some of the previous symbols from both sides. This not only causes a traditional PLNC to fail but also a simple one equalizer system will not solve the problem. Three main methods have been proposed by other researchers. The OFDM based PLNC is the simplest in terms of implementation and complexity but suffers from the disadvantages of the OFDMlike cyclic prefix overhead and frequency offset. The main disadvantage, however is the relatively low BER performance because it is restricted to linear equalizers in the PLNC system. Another approach is pre-filtering or pre-equalization. This method also has some disadvantages like complexity, sensitivity to channel variation and the need of a feedback channel for both end nodes. Finally, the maximum likelihood sequence detector was also proposed but is restricted to BPSK modulation and exponentially rising complexity are major drawbacks. The philosophy in this work is to avoid these disadvantages by using a time domain based system. The DFE is the equalizer of choice here because it provides a non-trivial BER performance improvement with very little increase in complexity. In this thesis, the problem of frequency selective channels in PLNC systems can be solved by properly adjusting the design of the system including the DFE. The other option is to redesign the equalizer to meet that goal. An AF DFE system is proposed in this work that provides very low complexity especially at the relay with little sensitivity to channel changes. A multi-antenna DNF DFE system is also proposed here with an improved performance. Finally, a new equalizer is designed for very low complexity and cost DNF approach with little sacrifice of BER performance. Matlab was used for the simulations with Monte Carlo method to verify the findings of this work through finding the BER performance of each system. This thesis opens the door for future improvement on the PLNC system. More research needs to be done like testing the proposed systems in real practical implementation and also the effect of adding channel coding to these systems.Iraqi Government, Ministry of Higher Educatio

Measurement and modelling of spectrum occupancy

Based on the conception of spectrum sharing, cognitive Radio as a promising technology for optimizing utilization of the radio spectrum has emerged to revolutionize the next generation wireless communications industry. In order to adopt this technology, the current spectrum allocation strategy has to be reformed and the real spectrum occupancy information has to be systemically investigated. To assess the feasibility of cognitive radio technology, the statistical information of the present spectral occupancy needs to be examined thoroughly, which forms the basis of the spectrum occupancy project. We studied the 100-2500 MHz spectrum with the traditional radio monitoring systems whose technical details have been fully recorded in this thesis. In order to detect the frequency agile signals, a channel sounder, which is capable of scanning 300 MHz spectrum within 4 ms with multiple channel inputs, was used as a dedicated radio receiver in our measurements. The conclusion of the statistical information from the spectrum monitoring experiments shows that the spectrum occupancy range from 100-2500 MHz are low indeed in the measuring locations and period. The average occupancies for most bands are less than 20%. Especially, the average occupancies in the 1 GHz to 2.5GHz spectrum are less than 5%. Time series analysis was initially introduced in spectrum occupancy analysis as a tool to model spectrum occupancy variations with time. For instance, the time series Airline model fits well the GSM band occupancy data. In this thesis, generalized linear models were used as complementarily solutions to model occupancy data into other parameters such as signal amplitude. The validation of the direction of arrival algorithms (EM and SAGE) was verified with the anechoic chamber, by which we can determine the spectrum occupancy in space domain

Advances in parameter estimation, source enumeration, and signal identification for wireless communications

Parameter estimation and signal identification play an important role in modern wireless communication systems. In this thesis, we address different parameter estimation and signal identification problems in conjunction with the Internet of Things (IoT), cognitive radio systems, and high speed mobile communications. The focus of Chapter 2 of this thesis is to develop a new uplink multiple access (MA) scheme for the IoT in order to support ubiquitous massive uplink connectivity for devices with sporadic traffic pattern and short packet size. The proposed uplink MA scheme removes the Media Access Control (MAC) address through the signal identification algorithms which are employed at the gateway. The focus of Chapter 3 of this thesis is to develop different maximum Doppler spread (MDS) estimators in multiple-input multiple-output (MIMO) frequency-selective fading channel. The main idea behind the proposed estimators is to reduce the computational complexity while increasing system capacity. The focus of Chapter 4 and Chapter 5 of this thesis is to develop different antenna enumeration algorithms and signal-to-noise ratio (SNR) estimators in MIMO timevarying fading channels, respectively. The main idea is to develop low-complexity algorithms and estimators which are robust to channel impairments. The focus of Chapter 6 of this thesis is to develop a low-complexity space-time block codes (STBC)s identification algorithms for cognitive radio systems. The goal is to design an algorithm that is robust to time-frequency transmission impairments