Enhancement in Channel Equalization Using Particle Swarm Optimization Techniques

This work proposes an improved inertia weight update method and position update method in Particle Swarm Optimization (PSO) to enhance the convergence and mean square error of channel equalizer. The search abilities of PSO are managed by the key parameter Inertia Weight (IW). A higher value leads to global search whereas a smaller value shifts the search to local which makes convergence faster. Different approaches are reported in literature to improve PSO by modifying inertia weight. This work investigates the performance of the existing PSO variants related to time varying inertia weight methods and proposes new strategies to improve the convergence and mean square error of channel equalizer. Also the position update method in PSO is modified to achieve better convergence in channel equalization. The simulation presents the enhanced performance of the proposed techniques in transversal and decision feedback models. The simulation results also analyze the superiority in linear and nonlinear channel conditions.

Fast Fading Channel Neural Equalization Using Levenberg-Marquardt Training Algorithm and Pulse Shaping Filters

Artificial Neural Network (ANN) equalizers have been successfully applied to mitigate Inter symbolic Interference (ISI) due to distortions introduced by linear or nonlinear communication channels. The ANN architecture is chosen according to the type of ISI produced by fixed, fast or slow fading channels. In this work, we propose a combination of two techniques in order to minimize ISI yield by fast fading channels, i.e., pulse shape filtering and ANN equalizer. Levenberg-Marquardt algorithm is used to update the synaptic weights of an ANN comprise only by two recurrent perceptrons. The proposed system outperformed more complex structures such as those based on Kalman filtering approach.

Frequency domain decision feedback equalizer for time-reversal space-time block coding

In this paper, a frequency domain decision feedback equalizer is proposed for single carrier transmission with time-reversal space-time block coding （TR-STBC）. It is shown that the diagonal decision feedback equalizer matrix can be calculated from the frequency domain channel response. Under the perfect feedback assumption, the proposed equalizer can approach matched filter bound （MFB）. Compared with the existing time domain decision feedback equalizer, the proposed equalizer exhibits better performance with the same equalization complexity.

A 6.25 Gb/s equalizer in 0.18μm CMOS technology for high-speed SerDes

This paper presents a 0.18μm CMOS 6.25 Gb/s equalizer for high speed backplane communication. The proposed equalizer is a combined one consisting of a one-tap feed-forward equalizer （FFE） and a two-tap half-rate decision feedback equalizer （DFE） in order to cancel both pre-cursor and post-cursor ISI. By employing an active-inductive peaking circuit for the delay line, the bandwidth of the FFE is increased and the area cost is minimized. CML-based circuits such as DFFs, summers and multiplexes all help to improve the speed of DFEs. Measurement results illustrate that the equalizer operates well when equalizing 6.25 Gb/s data is passed over a 30-inch channel with a loss of 22 dB and consumes 55.8 mW with the supply voltage of 1.8 V. The overall chip area including pads is 0.3 × 0.5 mm^2.

A novel differential multiuser detection algorithm for multiuser MIMO-OFDM systems

We propose an efficient low bit error rate(BER) and low complexity multiple-input multiple-output(MIMO) multiuser detection(MUD) method for use with multiuser MIMO orthogonal frequency division multiplexing(OFDM) systems.It is a hybrid method combining a multiuser-interference-cancellation-based decision feedback equalizer using error feedback filter(MIMO MIC DFE-EFF) and a differential algorithm.The proposed method,termed 'MIMO MIC DFE-EFF with a differential algorithm' for short,has a multiuser feedback structure.We describe the schemes of MIMO MIC DFE-EFF and MIMO MIC DFE-EFF with a differential algorithm,and compare their minimum mean square error(MMSE) performance and computational complexity.Simulation results show that a significant performance gain can be achieved by employing the MIMO MIC DFE-EFF detection algorithm in the context of a multiuser MIMO-OFDM system over frequency selective Rayleigh channel.MIMO MIC DFE-EFF with the differential algorithm improves both computational efficiency and BER performance in a multistage structure relative to conventional DFE-EFF,though there is a small reduction in system performance compared with MIMO MIC DFE-EFF without the differential algorithm.