Low Complexity Adaptive Noise Canceller for Mobile Phones Based Remote Health Monitoring

Mobile phones are gaining acceptance to become an effective tool for remote health monitoring. On one hand, during electrocardiographic (ECG) recording, the presence of various forms of noise is inevitable. On the other hand, algorithms for adaptive noise cancellation must be shared by limited computational power offered by the mobile phones. This paper describes a new adaptive noise canceller scheme, with low computational complexity, for simultaneous cancellation of various forms of noise in ECG signal. The proposed scheme is comprised of two stages. The first stage uses an adaptive notch filters, which are used to eliminate power-line interference from the primary and reference input signals, whereas the other noises are reduced using modified LMS algorithm in the second stage. Low power consumption and lower silicon area are key issues in mobile phones based adaptive noise cancellation. The reduction in complexity is obtained by using log-log LMS algorithm for updating adaptive filters in the proposed scheme. A comprehensive complexity and performance analysis between the proposed and traditional schemes are provided.DOI:http://dx.doi.org/10.11591/ijece.v4i3.553

A Study into Speech Enhancement Techniques in Adverse Environment

This dissertation developed speech enhancement techniques that improve the speech quality in applications such as mobile communications, teleconferencing and smart loudspeakers. For these applications it is necessary to suppress noise and reverberation. Thus the contribution in this dissertation is twofold: single channel speech enhancement system which exploits the temporal and spectral diversity of the received microphone signal for noise suppression and multi-channel speech enhancement method with the ability to employ spatial diversity to reduce reverberation

Integrated Filters and Couplers for Next Generation Wireless Tranceivers

The main focus of this thesis is to investigate the critical nonlinear distortion issues affecting RF/Microwave components such as power amplifiers (PA) and develop new and improved solutions that will improve efficiency and linearity of next generation RF/Microwave mobile wireless communication systems. This research involves evaluating the nonlinear distortions in PA for different analog and digital signals which have been a major concern. The second harmonic injection technique is explored and used to effectively suppress nonlinear distortions. This method consists of simultaneously feeding back the second harmonics at the output of the power amplifier (PA) into the input of the PA. Simulated and measured results show improved linearity results. However, for increasing frequency bandwidth, the suppression abilities reduced which is a limitation for 4G LTE and 5G networks that require larger bandwidth (above 5 MHz). This thesis explores creative ways to deal with this major drawback. The injection technique was modified with the aid of a well-designed band-stop filter. The compact narrowband notch filter designed was able to suppress nonlinear distortions very effectively when used before the PA. The notch filter is also integrated in the injection technique for LTE carrier aggregation (CA) with multiple carriers and significant improvement in nonlinear distortion performance was observed. This thesis also considers maximizing efficiency alongside with improved linearity performance. To improve on the efficiency performance of the PA, the balanced PA configuration was investigated. However, another major challenge was that the couplers used in this configuration are very large in size at the desired operating frequency. In this thesis, this problem was solved by designing a compact branch line coupler. The novel coupler was simulated, fabricated and measured with performance comparable to its conventional equivalent and the coupler achieved substantial size reduction over others. The coupler is implemented in the balanced PA configuration giving improved input and output matching abilities. The proposed balanced PA is also implemented in 4G LTE and 5G wireless transmitters. This thesis provides simulation and measured results for all balanced PA cases with substantial efficiency and linearity improvements observed even for higher bandwidths (above 5 MHz). Additionally, the coupler is successfully integrated with rectifiers for improved energy harvesting performance and gave improved RF-dc conversion efficienc

A robust approach for acoustic noise suppression in speech using ANFIS

The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application area of non-linear noise and interference suppression. This structure used is called an Adaptive Neuro Fuzzy Inference System (ANFIS). This system finds practical use mainly in audio telephone (mobile) communication in a noisy environment (transport, production halls, sports matches, etc). Experimental methods based on the two-input adaptive noise cancellation concept was clearly outlined. Within the experiments carried out, the authors created, based on the ANFIS structure, a comprehensive system for adaptive suppression of unwanted background interference that occurs in audio communication and degrades the audio signal. The system designed has been tested on real voice signals. This article presents the investigation and comparison amongst three distinct approaches to noise cancellation in speech; they are LMS (least mean squares) and RLS (recursive least squares) adaptive filtering and ANFIS. A careful review of literatures indicated the importance of non-linear adaptive algorithms over linear ones in noise cancellation. It was concluded that the ANFIS approach had the overall best performance as it efficiently cancelled noise even in highly noise-degraded speech. Results were drawn from the successful experimentation, subjective-based tests were used to analyse their comparative performance while objective tests were used to validate them. Implementation of algorithms was experimentally carried out in Matlab to justify the claims and determine their relative performances.Web of Science66631030

Noise Cancellation Employing Adaptive Digital Filters for Mobile Applications

The persistent improvement of the hybrid adaptive algorithms and the swift growth of signal processing chip enhanced the performance of signal processing technique exalted mobile telecommunication systems. The proposed Artificial Neural Network Hybrid Back Propagation Adaptive Algorithm (ANNHBPAA) for mobile applications exploits relationship among the pure speech signal and noise corrupted signal in order to estimate of the noise. An adaptive linear system responds for changes in its environment as it is operating. Linear networks are gets adjusted at each time step based on new input and target vectors can find weights and biases that minimize the networks sum squared error for recent input and target vectors. Networks of this kind are quite oftenly used for error cancellation, speech signal processing and control systems.    Noise in an audio signal has become major problem and hence mobile communication systems are demanding noise-free signal. In order to achieve noise-free signal various research communities have provided significant techniques. Adaptive noise cancellation (ANC) is a kind of technique which helps in estimation of un-wanted signal and removes them from corrupted signal. This paper introduces an Adaptive Filter Based Noise Cancellation System (AFNCS) that incorporates a hybrid back propagation learning for the adaptive noise cancellation in mobile applications. An extensive study has been made to explore the effects of different parameters, such as number of samples, number of filter coefficients, step size and noise level at the input on the performance of the adaptive noise cancelling system. The proposed hybrid algorithm consists all the significant features of Gradient Adaptive Lattice (GAL) and Least Mean Square (LMS) algorithms. The performance analysis of the method is performed by considering convergence complexity and bit error rate (BER) parameters along with performance analyzed with varying some parameters such as number of filter coefficients, step size, number of samples and input noise level. The outcomes suggest the errors are reduced significantly when the numbers of epochs are increased. Also incorporation of less hidden layers resulted in negligible computational delay along with effective utilization of memory. All the results have been obtained using computer simulations built on MATLAB platfor