Linear adaptive channel equalization for multiuser MIMO-OFDM systems

Linear adaptive channel equalization using the least mean square (LMS) algorithm and the recursive least-squares(RLS) algorithm for an innovative multi-user (MU) MIMOOFDM wireless broadband communications system is proposed. The proposed equalization method adaptively compensates the channel impairments caused by frequency selectivity in the propagation environment. Simulations for the proposed adaptive equalizer are conducted using a training sequence method to determine optimal performance through a comparative analysis. Results show an improvement of 0.15 in BER (at a SNR of 16 dB) when using Adaptive Equalization and RLS algorithm compared to the case in which no equalization is employed. In general, adaptive equalization using LMS and RLS algorithms showed to be significantly beneficial for MU-MIMO-OFDM systems.

Novel channel tracking and equalization methods in MU-MIMO-OFDM systems

The methodology undertaken, the channel model and the system model created for developing a novel adaptive equalization method and a novel channel tracking method for uplink of MU-MIMO-OFDM systems is presented in this paper. The results show that the channel tracking method works with 97% accuracy, while the training-based initial channel estimation method shows poor performance in estimating the actual channel comparatively.

Full-field feed-forward equalizer with adaptive system optimization

We numerically investigate the combination of full-field detection and feed-forward equalizer (FFE) for adaptive chromatic dispersion compensation up to 2160 km in a 10 Gbit/s on-off keyed optical transmission system. The technique, with respect to earlier reports, incorporates several important implementation modules, including the algorithm for adaptive equalization of the gain imbalance between the two receiver chains, compensation of phase misalignment of the asymmetric Mach-Zehnder interferometer, and simplified implementation of field calculation. We also show that in addition to enabling fast adaptation and simplification of field calculation, full-field FFE exhibits enhanced tolerance to the sampling phase misalignment and reduced sampling rate when compared to the full-field implementation using a dispersive transmission line.

Full-field feed-forward equalizer with adaptive system optimization

We numerically investigate the combination of full-field detection and feed-forward equalizer (FFE) for adaptive chromatic dispersion compensation up to 2160 km in a 10 Gbit/s on-off keyed optical transmission system. The technique, with respect to earlier reports, incorporates several important implementation modules, including the algorithm for adaptive equalization of the gain imbalance between the two receiver chains, compensation of phase misalignment of the asymmetric Mach-Zehnder interferometer, and simplified implementation of field calculation. We also show that in addition to enabling fast adaptation and simplification of field calculation, full-field FFE exhibits enhanced tolerance to the sampling phase misalignment and reduced sampling rate when compared to the full-field implementation using a dispersive transmission line.

Channel tracking in SDMA-based multi-user MIMO-OFDM communications systems

Capacity of current and future high data rate wireless communications depend significantly on how well changes in the wireless channel are predicted and tracked. Generally, this can be estimated by transmitting known symbols. However, this increases overheads if the channel varies over time. Given today’s bandwidth demand and the increased necessity for mobile wireless devices, the contributions of this research are very significant. This study has developed a novel and efficient channel tracking algorithm that can recursively update the channel estimation for wireless broadband communications reducing overheads, therefore increasing the speed of wireless communication systems.

Equalização neural aplicada a sistemas com modulação bidimensional em fibra óptica

Nowadays, optic fiber is one of the most used communication methods, mainly due to the fact that the data transmission rates of those systems exceed all of the other means of digital communication. Despite the great advantage, there are problems that prevent full utilization of the optical channel: by increasing the transmission speed and the distances involved, the data is subjected to non-linear inter symbolic interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to solve this problem, they compensate non-ideal responses of the channel in order to restore the signal that was transmitted. This work proposes an equalizer based on artificial neural networks and evaluates its performance in optical communication systems. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques

A mixed cost-function adaptive algorithm for ADSL time-domain equalization

We propose a mixed cost-function adaptive initialization algorithm for the time domain equalizer in a discrete multitone (DMT)-based asymmetric digital subscriber line. Using our approach, a higher convergence rate than that of the commonly used least-mean square algorithm is obtained, whilst attaining bit rates close to the optimum maximum shortening SNR and the upper bound SNR. Furthermore, our proposed method outperforms the minimum mean-squared error design for a range of time domain equalizer (TEQ) filter lengths. The improved performance outweighs the small increase in computational complexity required. A block variant of our proposed algorithm is also presented to overcome the increased latency imposed on the feedback path of the adaptive system.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Injection Locked Clocking and Transmitter Equalization Techniques for Chip to Chip Interconnects

Semiconductor technology scaling has enabled drastic growth in the computational capacity of integrated circuits (ICs). This constant growth drives an increasing demand for high bandwidth communication between ICs. Electrical channel bandwidth has not been able to keep up with this demand, making I/O link design more challenging. Interconnects which employ optical channels have negligible frequency dependent loss and provide a potential solution to this I/O bandwidth problem. Apart from the type of channel, efficient high-speed communication also relies on generation and distribution of multi-phase, high-speed, and high-quality clock signals. In the multi-gigahertz frequency range, conventional clocking techniques have encountered several design challenges in terms of power consumption, skew and jitter. Injection-locking is a promising technique to address these design challenges for gigahertz clocking. However, its small locking range has been a major contributor in preventing its ubiquitous acceptance.

In the first part of this dissertation we describe a wideband injection locking scheme in an LC oscillator. Phase locked loop (PLL) and injection locking elements are combined symbiotically to achieve wide locking range while retaining the simplicity of the latter. This method does not require a phase frequency detector or a loop filter to achieve phase lock. A mathematical analysis of the system is presented and the expression for new locking range is derived. A locking range of 13.4 GHz–17.2 GHz (25%) and an average jitter tracking bandwidth of up to 400 MHz are measured in a high-Q LC oscillator. This architecture is used to generate quadrature phases from a single clock without any frequency division. It also provides high frequency jitter filtering while retaining the low frequency correlated jitter essential for forwarded clock receivers.

To improve the locking range of an injection locked ring oscillator; QLL (Quadrature locked loop) is introduced. The inherent dynamics of injection locked quadrature ring oscillator are used to improve its locking range from 5% (7-7.4GHz) to 90% (4-11GHz). The QLL is used to generate accurate clock phases for a four channel optical receiver using a forwarded clock at quarter-rate. The QLL drives an injection locked oscillator (ILO) at each channel without any repeaters for local quadrature clock generation. Each local ILO has deskew capability for phase alignment. The optical-receiver uses the inherent frequency to voltage conversion provided by the QLL to dynamically body bias its devices. A wide locking range of the QLL helps to achieve a reliable data-rate of 16-32Gb/s and adaptive body biasing aids in maintaining an ultra-low power consumption of 153pJ/bit.

From the optical receiver we move on to discussing a non-linear equalization technique for a vertical-cavity surface-emitting laser (VCSEL) based optical transmitter, to enable low-power, high-speed optical transmission. A non-linear time domain optical model of the VCSEL is built and evaluated for accuracy. The modelling shows that, while conventional FIR-based pre-emphasis works well for LTI electrical channels, it is not optimum for the non-linear optical frequency response of the VCSEL. Based on the simulations of the model an optimum equalization methodology is derived. The equalization technique is used to achieve a data-rate of 20Gb/s with power efficiency of 0.77pJ/bit.

HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels

In this paper we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training based method with the same training information used, and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.

Amplitude banded RLS approach to time variant channel equalization

This paper proposes a non-linear adaptive algorithm, the amplitude banded RLS (ABRLS) algorithm, as an adaptation procedure for time variant channel equalizers. In the ABRLS algorithm, a coefficient matrix is updated based on the amplitude level of the received sequence. To enhance the capability of tracking for the ABRLS algorithm, a parallel adaptation scheme is utilized which involves the structures of decision feedback equalizer (DFE). Computer simulations demonstrate that the novel ABRLS based equalizer provides a significant improvement relative to the conventional RLS DFE on a rapidly time variant communication channel.