Edmund M-K. Lai

Filter Bank Channelizers for Multi-Standard Software Defined Radio Receivers

The ability to support multiple channels of different communication standards, in the available bandwidth, is of importance in modern software defined radio (SDR) receivers. An SDR receiver typically employs a channelizer to extract multiple narrowband channels from the received wideband signal using digital filter banks. Since the filter bank channelizer is placed immediately after the analog-to-digital converter (ADC), it must operate at the highest sampling rate in the digital front-end of the receiver. Therefore, computationally efficient low complexity architectures are required for the implementation of the channelizer. The compatibility of the filter bank with different communication standards requires dynamic reconfigurability. The design and realization of dynamically reconfigurable, low complexity filter banks for SDR receivers is a challenging task. This paper reviews some of the existing digital filter bank designs and investigates the potential of these filter banks for channelization in multi-standard SDR receivers. We also review two low complexity, reconfigurable filter bank architectures for SDR channelizers based respectively on the frequency response masking technique and a novel coefficient decimation technique, proposed by us recently. These filter bank architectures outperform existing ones in terms of both dynamic reconfigurability and complexity.

Low-Complexity Reconfigurable Fast Filter Bank for Multi-Standard Wireless Receivers

This brief presents a new low-complexity reconfigurable fast filter bank (RFFB) for wireless communication applications such as spectrum sensing and channelization. In RFFB, the bandwidth and center frequency of sub-bands can be varied with high frequency resolution without hardware reimplementation. This is achieved with an improved modified frequency transformation-based variable digital filter (MFT-VDF) at the first stage of the proposed multistage implementation. Existing second-order frequency transformation-based low-pass VDFs have limited cutoff frequency range which is approximately 12.5% of the sampling frequency. The proposed low-pass MFT-VDF offers unabridged control over the cutoff frequency on a wide frequency range thereby, improving the cutoff frequency range of existing VDFs. The design example shows that the RFFB is easy to design and offers substantial savings in gate counts over other filter banks.

Efficient Implementation of Reconfigurable Warped Digital Filters With Variable Low-Pass, High-Pass, Bandpass, and Bandstop Responses

In this brief, an efficient implementation of reconfigurable warped digital filter with variable low-pass, high-pass, bandpass, and bandstop responses is presented. The warped filters, obtained by replacing each unit delay of a digital filter with an all-pass filter, are widely used for various audio processing applications. However, warped filters require first-order all-pass transformation to obtain variable low-pass or high-pass responses, and second-order all-pass transformation to obtain variable bandpass or bandstop responses. To overcome this drawback, the proposed method combines the warped filters with the coefficient decimation technique. The proposed architecture provides variable low-pass or high-pass responses with fine control over cut-off frequency and variable bandwidth bandpass or bandstop responses at an arbitrary center frequency without updating the filter coefficients or filter structure. The design example shows that the proposed variable digital filter is simple to design and offers substantial savings in gate counts and power consumption over other approaches.

Power quality indices of Compact Fluorescent Lamps for residential use — A New Zealand study

This paper discusses the power quality indices of Compact Fluorescent Lamps (CFLs) used in residential lighting. Harmonic indices are important factors when analyzing residential power quality. Research carried out in the recent past has highlighted power quality issues relating to CFLs. The experiments performed by us confirmed the stated issues. Most brands tested had low power factor associated with high harmonic current levels. A few high power factor products with low harmonic current levels also exist and were highlighted in this research.

A Greedy Common Subexpression Elimination Algorithm for Implementing FIR Filters

The complexity of finite impulse response (FIR) filters is dominated by the number of adders (subtractors) used to implement the coefficient multipliers. A greedy common subexpression elimination (CSE) algorithm with a look-ahead method based on the canonic signed digit (CSD) representation of filter coefficients for implementing low complexity FIR filters is proposed in this paper. Our look-ahead algorithm chooses the maximum number of frequently occurring common subexpressions and hence reduces the number of adders required to implement the filter. This adder reduction is achieved without any increase in critical path length. Design examples of FIR filters show that the proposed method offers an average adder reduction of about 20% over the best known CSE method.

Linear-Phase VDF Design With Unabridged Bandwidth Control Over the Nyquist Band

This brief presents a low-complexity linear-phase variable digital filter (VDF) design with tunable lowpass (LP), highpass (HP), bandpass (BP), and bandstop (BS) responses anywhere over the entire Nyquist band. The spectral-parameter-approximation-based VDFs (SPA-VDFs) was designed using the Farrow structure and has advantages of linear phase, lower group delay, and fewer variable multipliers. However, the total gate count and the dynamic range of filter coefficient values of SPA-VDFs significantly increase with the tunable range of cutoff frequency, which limits their usefulness in emerging signal processing and wireless communication applications. In addition, existing VDFs need to update either filter coefficients or need parallel filter structures to obtain variable LP, HP, BP and BS responses. In this brief, a new VDF design is proposed by deftly integrating SPA-VDF with the modified coefficient decimation method (MCDM), and it will be referred to as SPA-MCDM-VDF. The SPA-MCDM-VDF provides LP, HP, BP, and BS responses with unabridged center frequency and bandwidth control over the entire Nyquist band without the need for hardware reimplementation or coefficient update. The complexity comparisons show that the SPA-MCDM-VDF offers substantial savings in gate count, group delay, and number of variable multiplications over other linear-phase VDFs.

Quantization effects on Compressed Sensing Video

Compressed Video Sensing (CVS) is the application of the theory and principles of Compressed Sensing to video coding. Previous research has largely ignored the effects of quantization on the random measurements. In this paper, we showed that Gaussian quantization of the CVS coefficients produce higher quality reconstructed videos compared to using MPEG and uniform quantization. Furthermore, the quantization matrix is robust against variations in the mean and standard deviations of the CS measurements among frames. Our work shows how quantization can be implemented for a practical CVS codec.

Distributed Video Coding Based on Compressed Sensing

Compressed Sensing (CS) is a new approach to signal acquisition that can potentially allow us to design very simple video encoders that can be implemented on mobile devices with limited resources. However, previously proposed CS based video codec either require a conventional video codec or a feedback channel for effective operation, thus increasing the complexity. In this paper, a distributed Compressed Video Sensing codec is proposed that only makes use of CS at the encoder. A novel Side Information generation scheme is incorporated in the decoder which exploits the correlation between CS measurements of nearby frames. It is much simpler than other schemes found in the literature and yet effective. Simulation results demonstrate that effective video coding can be achieved using this codec.

A cerebellar associative memory approach to option pricing and arbitrage trading

Option pricing is a process to obtain the theoretical fair value of an option based on the factors affecting its price. The classical approaches to option pricing include the Black-Scholes pricing formula and the binomial pricing model. These techniques, however, employ complex and rigid statistical formulations that are not easily comprehensible to novice investors. More recently, non-parametric and computational methods of option valuation that are able to construct a model of the pricing formula from historical data have been proposed in the literature. However, most of these models functioned as black-boxes and may not be able to efficiently and accurately capture the complex market dynamics and characteristics of the option data. This paper proposes a novel brain-inspired cerebellar associative memory model for pricing American-style call options on British pound vs. US dollar currency futures. The proposed model, named PSECMAC, constitutes a local learning model that is inspired by the neurophysiological aspects of the human cerebellum. The PSECMAC-based option-pricing model is subsequently applied in a mis-priced option arbitrage trading system. Simulation results show an encouraging return on investment of 23.1% for some of the traded options.

Image resizing and rotation based on the consistent resampling theory

The recently proposed consistent resampling theory for non-bandlimited signals is applied to image resizing and rotation. Images with high frequency components can be resampled using this scheme to achieve high quality performance. Image resizing is treated as resampling using non-ideal interpolation functions. Both zoom in and zoom out by non-integer factors are considered. Image rotation is also formulated as a resampling process. We show that our approach outperforms other linear image processing techniques without increasing the computational cost.