SGD Frequency-Domain Space-Frequency Semiblind Multiuser Receiver with an Adaptive Optimal Mixing Parameter

A novel stochastic gradient descent frequency-domain (FD) space-frequency (SF) semiblind multiuser receiver with an adaptive optimal mixing parameter is proposed to improve performance of FD semiblind multiuser receivers with a fixed mixing parameters and reduces computational complexity of suboptimal FD semiblind multiuser receivers in SFBC downlink MIMO MC-CDMA systems where various numbers of users exist. The receiver exploits an adaptive mixing parameter to mix information ratio between the training-based mode and the blind-based mode. Analytical results prove that the optimal mixing parameter value relies on power and number of active loaded users existing in the system. Computer simulation results show that when the mixing parameter is adapted closely to the optimal mixing parameter value, the performance of the receiver outperforms existing FD SF adaptive step-size (AS) LMS semiblind based with a fixed mixing parameter and conventional FD SF AS-LMS training-based multiuser receivers in the MSE, SER and signal to interference plus noise ratio in both static and dynamic environments

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Space-time coding for CDMA-based wireless communication systems

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2002Includes bibliographical references (leaves: 72-75)Text in English; Abstract: Turkish and Englishx, 75 leavesMultiple transmit antennas giving rise to diversity (transmit diversity) have been shown to increase downlink (base station to the mobile) capacity in cellular systems.The third generation partnership project (3GPP) for WCDMA has chosen space time transmit diversity (STTD) as the open loop transmit diversity technique for two transmit antennas.On the other hand, the CDMA 2000 has chosen space time spreading (STS) and orthogonal transmit diversity (OTD) as the open loop transmit diversity.In addition to all the standardization aspects, proposed contributions such as space time coding assisted double spread rake receiver (STC-DS-RR) are exist.In this thesis, open loop transmit diversity techniques of 3GPP, CDMA 2000 and existing contributions are investigated.Their performances are compared as a means of biterror- rate (BER) versus signal-to-noise ratio (SNR)

Multi-carrier CDMA using convolutional coding and interference cancellation

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN016251 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Performance Optimization Over Wireless Links With Operating Constraints

Wireless communication is one of the most active areas of technological innovations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabilities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and networks depend on their adaptation capability which in turn presents many new technical challenges in hardware and protocol design, power management, interference metrics, distributed algorithms, Quality of Service (QoS) requirements arid security issues. Transmitter adaptation methods have gained importance, and numerous transmitter optimization algorithms have been proposed in recent years. The main idea behind these algorithms is to optimize the transmitted signals according to the patterns of interference in the operating environment such that some specific criterion is optimized. In this context, the objective of this dissertation is to propose transmitter adaptation algorithms in conjunction with power control for wireless systems focusing on performance optimization based on operating constraints. Specifically, this dissertation achieves joint transmitter adaptation and power control in the uplink and downlink of wireless systems with applications to Multiple-Input-Multiple-Output (MIMO) wireless systems and cognitive radio networks. In addition, performance of the proposed algorithms are evaluated in the context of fading channels, taking into consideration the time-varying nature of wireless channels

Techniques d’Estimation de Canal et de Décalage de Fréquence Porteuse pour Systèmes Sans-fil Multiporteuses en Liaison Montante

Multicarrier modulation is the common feature of high-data rate mobile wireless systems. In that case, two phenomena disturb the symbol detection. Firstly, due to the relative transmitter-receiver motion and a difference between the local oscillator (LO) frequency at the transmitter and the receiver, a carrier frequency offset (CFO) affects the received signal. This leads to an intercarrier interference (ICI). Secondly, several versions of the transmitted signal are received due to the wireless propagation channel. These unwanted phenomena must be taken into account when designing a receiver. As estimating the multipath channel and the CFO is essential, this PhD deals with several CFO and channel estimation methods based on optimal filtering. Firstly, as the estimation issue is nonlinear, we suggest using the extended Kalman filter (EKF). It is based on a local linearization of the equations around the last state estimate. However, this approach requires a linearization based on calculations of Jacobians and Hessians matrices and may not be a sufficient description of the nonlinearity. For these reasons, we can consider the sigma-point Kalman filter (SPKF), namely the unscented Kalman Filter (UKF) and the central difference Kalman filter (CDKF). The UKF is based on the unscented transformation whereas the CDKF is based on the second order Sterling polynomial interpolation formula. Nevertheless, the above methods require an exact and accurate a priori system model as well as perfect knowledge of the additive measurementnoise statistics. Therefore, we propose to use the H∞ filtering, which is known to be more robust to uncertainties than Kalman filtering. As the state-space representation of the system is non-linear, we first evaluate the “extended H∞ filter”, which is based on a linearization of the state-space equations like the EKF. As an alternative, the “unscented H∞ filter”, which has been recently proposed in the literature, is implemented by embedding the unscented transformation into the “extended H∞ filter” and carrying out the filtering by using the statistical linear error propagation approach.Multicarrier modulation is the common feature of high-data rate mobile wireless systems. In that case, two phenomena disturb the symbol detection. Firstly, due to the relative transmitter-receiver motion and a difference between the local oscillator (LO) frequency at the transmitter and the receiver, a carrier frequency offset (CFO) affects the received signal. This leads to an intercarrier interference (ICI). Secondly, several versions of the transmitted signal are received due to the wireless propagation channel. These unwanted phenomena must be taken into account when designing a receiver. As estimating the multipath channel and the CFO is essential, this PhD deals with several CFO and channel estimation methods based on optimal filtering. Firstly, as the estimation issue is nonlinear, we suggest using the extended Kalman filter (EKF). It is based on a local linearization of the equations around the last state estimate. However, this approach requires a linearization based on calculations of Jacobians and Hessians matrices and may not be a sufficient description of the nonlinearity. For these reasons, we can consider the sigma-point Kalman filter (SPKF), namely the unscented Kalman Filter (UKF) and the central difference Kalman filter (CDKF). The UKF is based on the unscented transformation whereas the CDKF is based on the second order Sterling polynomial interpolation formula. Nevertheless, the above methods require an exact and accurate a priori system model as well as perfect knowledge of the additive measurementnoise statistics. Therefore, we propose to use the H∞ filtering, which is known to be more robust to uncertainties than Kalman filtering. As the state-space representation of the system is non-linear, we first evaluate the “extended H∞ filter”, which is based on a linearization of the state-space equations like the EKF. As an alternative, the “unscented H∞ filter”, which has been recently proposed in the literature, is implemented by embedding the unscented transformation into the “extended H∞ filter” and carrying out the filtering by using the statistical linear error propagation approach