Bit error rate estimation in WiMAX communications at vehicular speeds using Nakagami-m fading model

The wireless communication industry has experienced a rapid technological evolution from its basic first generation (1G) wireless systems to the latest fourth generation (4G) wireless broadband systems. Wireless broadband systems are becoming increasingly popular with consumers and the technological strength of 4G has played a major role behind the success of wireless broadband systems. The IEEE 802.16m standard of the Worldwide Interoperability for Microwave Access (WiMAX) has been accepted as a 4G standard by the Institute of Electrical and Electronics Engineers in 2011. The IEEE 802.16m is fully optimised for wireless communications in fixed environments and can deliver very high throughput and excellent quality of service. In mobile communication environments however, WiMAX consumers experience a graceful degradation of service as a direct function of vehicular speeds. At high vehicular speeds, the throughput drops in WiMAX systems and unless proactive measures such as forward error control and packet size optimisation are adopted and properly adjusted, many applications cannot be facilitated at high vehicular speeds in WiMAX communications. For any proactive measure, bit error rate estimation as a function of vehicular speed, serves as a useful tool. In this thesis, we present an analytical model for bit error rate estimation in WiMAX communications using the Nakagami-m fading model. We also show, through an analysis of the data collected from a practical WiMAX system, that the Nakagami-m model can be made adaptive as a function of speed, to represent fading in fixed environments as well as mobile environments

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency

Detection of OFDM Signals Using Pilot Tones and Applications to Spectrum Sensing for Cognitive Radio Systems

Nowadays there are an increasing number of wireless devices which support wireless networking and the need for higher data rate communication is increasing rabidly. As more and more systems go wireless, approaching technologies will face spectral crowding and existence of wireless devices will be an important issue. Because of the limited bandwidth availability, accepting the request for higher capacity and data rates is a challenging task, demanding advanced technologies that can offers new methods of using the available radio spectrum. Cognitive radio introduces a key solution to the spectral increasing issue by presenting the opportunistic usage of spectrum that is not heavily occupied by licensed users. It is a latest idea in wireless communications systems which objective to have more adaptive and aware communication devices which can make better use of available natural resources. Cognitive radio appears to be an attractive solution to the spectral congestion problem by introducing the notion of opportunistic spectrum use. Cognitive radios can operate as a secondary systems on top of existence system which are called primary (or licensed) systems. In this case, secondary (cognitive) users need to detect the unused spectrum in order to be able to access it. Because of its many advantages, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. It\u27s shown 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. Researches show that OFDM technique is considered as a candidate for cognitive radio systems. The objective of this dissertation is to explore detecting of OFDM modulated signals using pilot tones information. Specifically we applying Time-Domain Symbol Cross-Correlation (TDSC) method in the confect of actual 4G wireless standards such as WIMAX and LTE. This detection is only based upon the knowledge of pilot structures without knowledge of received signal so that, it can be performed on every portion of the received signal. The approach induces Cross-Correlation between pilots subcarriers and exploits the deterministic and periodic characteristics of pilot mapping in the time frequency domain

OPTIMIZING RADIO RESOURCE MANAGEMENT IN VERY BAD CHANNEL CONDITIONS

Radio resource management is one of the most important parts of modern multi-user wireless communication systems. The main reason for this importance comes from the fact that the radio resources, such as bandwidth and power, are scarce. For instance, UMTS systems use 5MHz bandwidth for voice as well as data services. The optimum usage of the radio resource guarantees the highest efficient utilization of wireless networks. To optimize the radio resources, the transmitters need to estimate the channel conditions. This channel estimation is done by using pilot signal from the receiver. There are usually small delays between the measurements and the radio resource allocation. When the channel is highly correlated, this delay will not affect the performance, because the channel will not be significantly changed between the time of measurement and the time of transmission. However, if the mobile speed is high or the channel is very high dynamic, the correlation becomes very low. This is due to the timevarying nature of the channel. We call channels with very low correlation in time as bad condition channels. In this thesis we discuss this extremely important topic. The tools for analyzing bad condition channels are also proposed and discussed. Two power control algorithms to mitigate the low correlation of channels have been proposed. Our algorithms are validated through several simulations.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Iterative Receiver for MIMO-OFDM System with ICI Cancellation and Channel Estimation

As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels

Extending TDL based non-WSSUS vehicle-to-everything channel model

In den vergangenen Jahrzehnten haben drahtlose Kommunikationssysteme eine rasante Entwicklung durchgemacht und es wurden viele Untersuchungen durchgeführt, seit Maxwell die Existenz von elektromagnetischer Wellen vorausgesagt hat. In den letzten Jahren hat die Forschung im Bereich der vehicle to X (V2X)-Kommunikation stetig zugenommen. V2X beschreibt die Fähigkeit, Daten zwischen einem Fahrzeug oder vehicle (V) und “allem” zu übertragen. In Zukunft könnten Fahrzeuge mit ihrer Umgebung kommunizieren, um Verkehrsunfälle zu vermeiden und Staus zu verringern. Dazu werden sie ihr Geschwindigkeits- und Positionsdaten über Ad-hoc-Fahrzeugnetze senden und empfangen können. Um die Verkehrssicherheit zu erhöhen, ist eine zuverlässige Kommunikationsverbindung notwendig. Die größte Herausforderung bei der Fahrzeugkommunikation besteht darin, dass sich die Eigenschaften des Physical Layers aufgrund der inhärenten Mobilität innerhalb des Kanals, der hohen Fahrzeuggeschwindigkeiten, der unterschiedlichen Antennenpositionen und der vielen Handover aufgrund kleinerer Zellen schnell ändern. Dies bringt eine Reihe von Herausforderungen in Bezug auf die Kanalcharakterisierung mit sich. Es handelt sich um einen Kanal mit starker Zeitvarianz und es treten viele Übergänge auf. Somit handelt es sich um einen nicht-stationärer (non-stationary) Kanal. Das Hauptziel dieser Untersuchung ist es, eine Methode zu finden, mit der der Kanal einer komplexen Umgebung in einer einfachen Form mit weniger strengen Beziehungen zur Geometrie dargestellt werden kann. Dabei werden die statistischen Eigenschaften ähnlich der Messdaten beibehalten. In dieser Arbeit werden nichtstationäre tapped delay line (TDL)-Modelle verwendet, um vehicle to infrastructure (V2I)-Kanäle zu beschreiben. Es wird eine neue Strategie zur Extraktion von TDL-Kanalmodellparametern aus Messdaten vorgeschlagen. Dieser Ansatz basiert auf einer bestehenden Methode zur Ableitung von Parametern für ein TDLModell. Es wird gezeigt, dass mit einer anderen Methode zur Auswahl der Taps die Anzahl der Abgriffe, die zur Rekonstruktion der root mean square delay spread (RMS-DS) eines Kanals erforderlich sind, erheblich reduziert werden kann. Ein neuer Ansatz zur überprüfen der Korrektheit der Ableitung der Kanalmodellparameter wird aufgezeigt. Die Durchführbarkeit der Methode wird anhand von Channel Sounding Messungen bestätigt. In dieser Dissertation wird ein Generator zur Erzeugung von Kanalimpulsantworten entwickelt und das nichtstationäre Verhalten der Kanäle durch die Verwendung eines ON/OFF-Prozesses beschrieben. Es werden Markov-Ketten unterschiedlicher Ordnung modelliert, um das nicht-stationäre Verhalten besser zu erfassen. Die Untersuchung zeigt, dass Markov-Ketten erster Ordnung mit zwei Zuständen vorzuziehen sind, um das häufige ON/OFF-Verhalten von Mehrwegpfaden darzustellen, und dass die Markov-Modelle zweiter und dritter Ordnung keine großen Auswirkungen haben. Eine Methode zur Erweiterung eines single input single output (SISO)-TDL-Modells auf multiple input multiple output (MIMO) unter der non-wide sense stationary uncorrelated scattering (non-WSSUS)-Annahme wird eingeführt, um TDL-Kanalmodelle für V2I MIMO-Systeme zu entwickeln. Die Analyse bewertet die SISO- mit der MIMO-Konfiguration in Bezug auf die Kanalkapazität. Es werden verschiedene MIMO-Konfigurationen untersucht, und es wird gezeigt, dass die Position der Antennen eine wichtige Rolle spielt. Die Verwendung von nur vier Antennen am transmitter (Tx) und receiver (Rx), die in unterschiedliche Richtungen abstrahlen, führt zu einem qualitativen Sprung in der Leistungsfähigkeit des Systems.In the past decades, wireless communication systems have undergone rapid development, and many investigations have been done since Maxwell predicted the existence of electromagnetic waves. In recent years, vehicle to X (V2X) communication research has been growing steadily. V2X describes the ability to transmit data between a vehicle (V) and “everything”. In the future, vehicles might be able to communicate with their environment to prevent traffic accidents and reduce congestion by allowing vehicles to transmit and receive data through a vehicular ad hoc network at their speed and position. In order to achieve the ultimate goal of enhancing transportation safety, it is crucial to establish reliable communication links. The main challenge of vehicular communications introduces new properties because the physical layer properties are rapidly changing due to inherent mobility within the channel, high vehicle speeds, varying antenna positions, and many handovers due to smaller cells. This brings up a number of challenges in terms of channel characterization because it is a strong time-variant channel and many transitions occur; therefore, it is a non-stationary channel. In this thesis, non-stationary tapped delay line (TDL) models are used to describe the vehicle to infrastructure (V2I) channels. This thesis proposes a new strategy to extract TDL channel model parameters from measurement data. The proposed approach is based on an existing method to derive parameters for a TDL model. It will be shown that with a different method of choosing taps, the number of taps necessary to regenerate the root mean square delay spread (RMS-DS) of a channel can be significantly reduced. An approach is proposed to verify the correctness of the channel model parameters derivation. The feasibility of the method will be confirmed using channel-sounding measurements. This dissertation devises a generator to produce channel impulse responses (CIRs) and describes the non-stationary behavior of the channels via employing an ON/OFF process. Different order Markov chains are modeled with the aim of better capturing the non-stationary behavior. The investigation shows that first-order two-state Markov chains are preferable to represent multipath’s frequent ON/OFF behavior, and the second- and third-order Markov models do not make enormous effects. A method for extending a single input single output (SISO)-TDL model to multiple input multiple output (MIMO) under non-wide sense stationary uncorrelated scattering (non-WSSUS) assumption is introduced to develop TDL channel models for the V2I MIMO systems. The analysis evaluates SISO- with MIMO configuration in terms of channel capacity. Different MIMO configurations are explored, and it will be illustrated that the position of antennas plays an important role. Using only four antennas at the transmitter (Tx) and receiver (Rx) that radiate towards different directions will make a qualitative leap in the performance of the system