Muhammad Zeeshan

Efficient Target Detection and Joint Estimation of Target Parameters With a Two-Element Rotating Antenna

An algorithm is proposed for the detection and joint estimation of target parameters for a radar with a two-element rotating antenna. Rotation of the antenna introduces unwanted effects, which may cause inaccuracy in the parameter estimation. Target detection is performed by adding the processed data from two sensors. Joint estimation of range, Doppler, and direction of arrival (DOA) is carried while compensating the effects of antenna rotation. The detection performance is analyzed in terms of the receiver operating characteristics. Analytical expressions of Cramer-Rao Bound for Doppler, the range and DOA are derived. Computational complexity is also discussed. A simulation demonstrates and verifies the proposed algorithm and its analyses.

An efficient design of genetic algorithm based Adaptive Fuzzy Logic Controller for multivariable control of HVAC systems

In Heating, Ventilating and Air Conditioning (HVAC) systems, effective thermal management is required because energy and operation costs of buildings are directly influenced by how well an air-conditioning system performs. HVAC systems are typically nonlinear time varying with disturbances, where conventional PID controllers may trade-off between stability and rise time. To overcome this limitation, a Genetic Algorithm based Adaptive Fuzzy Logic Controller (AFLC) design has been proposed for the control of temperature and relative humidity of an experimental setup by manipulating valve positions to adjust the water and steam flow rates for Air Handling Unit (AHU). Modulating equal percentage Globe valves for chilled water and steam have been modeled according to exact flow rates of water and steam. A novel method for the adaptation of Fuzzy Logic Controller (FLC) by modifying Fuzzy Rule Matrix (FRM) based on Genetic Algorithm (GA) has been proposed. The proposed adaptive controller outperforms the existing fuzzy controller in terms of steady state error, rise time and settling time.

A fast convergence feed-forward automatic gain control algorithm based on RF characterization of Software Defined Radio

High throughput SDR networking waveforms require fast convergence Automatic Gain Control algorithms due to frequent transmissions in short time slots. In this paper, we propose a novel algorithm for feed-forward AGC with fast convergence and reduced computational complexity. Firstly, the RF front end of Software Defined Radio (SDR) is characterized through the use of vector signal generator. An RF characterization table consisting of Received Signal Strength Indicator (RSSI) values is constructed for selected values/ranges of gain and received power. Secondly, a comprehensive table is constructed through piece-wise analysis of the data obtained in first step and applying interpolation and curve-fitting techniques offline. By using the current RSSI and previous gain values, the received power is found using the constructed table. The working gain value, obtained from the same table, is then applied corresponding to the current received power. The actual convergence time of the proposed AGC algorithm is one clock cycle but it can be controlled through the use of loop filter.

Multivariable adaptive Fuzzy logic controller design based on genetic algorithm applied to HVAC systems

In Heating, Ventilating and Air Conditioning (HVAC) systems, effective thermal management is required because energy and operation costs of buildings are directly influenced by how well an air-conditioning system performs. HVAC systems are typically nonlinear time varying with disturbances, where conventional PID controllers may trade-off between stability and rise time. To overcome this limitation, a Genetic Algorithm based Adaptive Fuzzy Logic Controller (AFLC) design has been proposed for the control of temperature and relative humidity of an experimental setup by manipulating valve positions to adjust the water and steam flow rates for Air Handling Unit (AHU). Modulating equal percentage Globe valves for chilled water and steam have been modeled according to exact flow rates of water and steam. A novel method for the adaptation of Fuzzy Logic Controller (FLC) by modifying Fuzzy Rule Matrix (FRM) based on Genetic Algorithm (GA) has been proposed. The proposed adaptive controller outperforms the existing fuzzy controller in terms of steady state error, rise time and settling time.

Data aided algorithm for burst detection in wideband networking waveform with FPGA implementation on SDR platform

This paper presents a new technique for detection of bursts in a wideband networking waveform of a software defined radio. For burst mode of transmission, the timing synchronization includes the recovery of time varying sampling clock offset and the detection of start of burst. Both these operations are very important in wideband networking radio operation as they directly affect the Medium Access adaptive time slot algorithm. The proposed burst detection scheme computes the decision metric on the basis of a specially designed training sequence. The threshold value for the proposed burst detection metric is very less dependent on channel conditions. It is shown that both the proposed algorithms achieve better performance as compared to existing algorithms. Computationally efficient prototype hardware implementation on Field Programmable Gate Array (FPGA) is also presented. Real-time hardware results have been presented to demonstrate the effectiveness of the proposed algorithms and architecture for systems requiring high data throughput.

Comparative performance evaluation of LDPC coded and turbo coded OFDM systems in SUI multipath channel models

In this research paper, we carry out comparative performance evaluation of Low Density Parity- Check (LDPC) coded and Turbo coded orthogonal frequency division multiplexing (OFDM) systems by varying a number of parameters/factors including channel types, data block size, and number of decoding iterations. OFDM possesses the ability to counter sever channel conditions if coded with a suitable error correction scheme. LDPC coding is appearing as most promising combination in upcoming communication standards. The error rate behavior of LDPC coded OFDM system has been compared with its toughest competitor i.e. Turbo Coded OFDM system, especially on six Stanford University Interim (SUI) multipath channel models. Their computational complexities have also been worked out to evaluate the latency, efficiency, cost effect and ease of implementation.

Joint algorithm for burst detection and AGC improvement in high throughput software defined radio waveform

Abstract The SDR networking waveforms mostly use non-constant envelope modulation schemes at the physical layer requiring a stable AGC operation during envelope amplitude variations. Moreover, the size of network packets may vary form a single burst to multiple bursts requiring an AGC with fast convergence to reduce settling time overhead. In this paper, we propose a novel joint algorithm for both the burst detection and improvement of the convergence time and stability of a conventional AGC by using Zadoff-Chu sequence. A specifically designed repeated Zadoff-Chu sequence is used for the detection of burst and fixing the gain for the complete burst duration. The proposed algorithm is implemented on Field Programmable Gate Array (FPGA) on SDR platform. Results of both the simulation and implementation are shown to demonstrate the effectiveness of the proposed technique.

Prospective evaluation of frailty and functional independence in older adult trauma patients

BACKGROUND The aim of our study was to assess the association between frailty and functional status in geriatric trauma patients. METHODS 3-year(2013-2015) prospective analysis and included all geriatric trauma patients(≥65y) discharged to a single rehabilitation center from our level-I trauma center. Frailty was measured using Trauma-Specific-Frailty-Index(TSFI) while Functional status was assessed using functional-independence-measure(FIM) at admission and discharge from rehabilitation center. Multivariate linear regression analysis was performed. RESULTS 267 patients were enrolled. Mean age was 76.9 ± 7.1y, 63.6% were males. Overall, 22.8% were frail, and 37.4% were pre-frail. On linear regression, higher motor-FIM, higher cognitive-FIM scores at admission, and longer length-of-stay at rehab were independently associated with increased discharge FIM score. While, ISS(injury-severity-score), pre-frail and frail status were negatively correlated with FIM gain. CONCLUSION Frail patients were less likely to recover to their baseline functional status compared with non-frail patients. Early focused intervention in frail elderly patients is warranted to improve functional status in this population.

Adaptive equalization in hybrid DS-TH CDMA system using State-Space RLS with Adaptive Memory

Modern wireless communication networks need to support a variety of data intensive applications in various medium/channel scenarios. It requires high network throughput as well as robustness against Multiuser Interference (MUI), multipath fading and other channel effects. This is achieved by using the hybrid Direct Sequence Time Hopped CDMA (DS-TH CDMA) systems. In this paper, a novel usage of State-Space Recursive Least Squares with Adaptive Memory (SSRLSWAM) with non-coherent detection is proposed for adaptive equalization of DS-TH CDMA system. The proposed algorithm is able to mitigate multipath fading effects through adaptive equalization by effectively initializing the SSRLSWAM and tuning its forgetting factor. The choice to use non-coherent detection is made because of the fact that non-coherent detectors do not utilize the phase information at the receiver side, resulting in lowering computational complexity. The BER performance of the proposed algorithm is compared with the correlating detector and Minimum Mean Square Error (MMSE) detector. It is shown that SSRLSWAM results in BER performance better than both the correlating and MMSE.

Frequency Diversity Array for DOA Estimation

The localization of targets has been presented in this article. DOA (Direction of Arrival) is an important parameter to be determined by radar. The MLE (Maximum Likelihood Estimator) has been widely used to accurately and efficiently estimate the DOAs of multiple targets. The targets at different ranges result in a variation in amplitude of the received signals, so an MLE estimator has to operate at all ranges. For accurate results of DOA, the complex amplitudes of multiple targets should not be much different and also the prior information of Doppler and number of targets is required. In this paper, an approach is proposed which uses the classical 2D algorithm to estimate range, Doppler and number of targets and then FDA (Frequency Diversity Array) is used to focus power in a particular range. As a result, the MLE can get data from a particular range cell where all targets have almost same amplitude and thus MLE can accurately estimate the DOAs of multiple targets. Simulations and results have confirmed the effectiveness of proposed approach.