SPARSE ECHO CANCELLATION USING VARIANTS OF LEAST MEAN FOURTH AND LEAST MEAN SQUARE ALGORITHMS

Echo cancellation is the most essential and indispensable component of telephone networks. The impulse responses of most of the networks are sparse in nature; that is, the impulse response has a small percentage of its components with a significant magnitude (large energy), while the rest are zero or small. In these sparse environments, conventional adaptive algorithms like least mean square (LMS) and normalized LMS (NLMS) show substandard and inferior performances. In this paper, the performances of the normalized least mean square (NLMS) algorithm, the normalized least mean fourth (NLMF) and the proportionate normalized least mean fourth (PNLMF) are compared for sparse echo cancellation. The sparseness of both the echo response and the input signal is exploited in this algorithm to achieve improved results at a low computational cost. The PNLMF algorithm showed better results and faster convergence in sparse and non sparse systems, but its results in sparse environments are more impressive. The NLMF algorithm shows good results in sparse environments but not in non-sparse environments. The PNLMS algorithm can be considered superior to the NLMF and NLMS algorithms with respect to the error profile. A modified algorithm, the sparse controlled modified proportionate normalized LMF (SCMPNLMF) algorithm, is proposed, and its performances are compared with the other algorithms

PERFORMANCE OF OPTIMIZATION METHODS FOR ENERGY EFFICIENCY IN COOPERATIVE COMMUNICATION

In cooperative communication the effect of channel fading can be improved by cooperation between the user terminals and the relay nodes in wireless networks. In a Wireless Sensor Network (WSN), cooperative relaying improves the link quality with a relatively high Energy Efficiency Gain (EEG). In this paper, optimized parameters are used in WSN to enhance the EEG using particle swarm optimization (PSO) and Real-Coded Genetic Algorithm (RGA). Maximum enhancements of EEG obtained using RGA for M-ary Quadrature Amplitude Modulation (M-QAM) is 64% for M=16, 87% for M=32, and 97% for M=64 compared to EEG obtained without optimization. The superiority proposed optimization methods are verified by comparing with results without optimization and by comparing with the published results for Energy Efficiency (EE)

SC-FDMA Uplink System In Heavily Faded Areas With Low Signal-To-Noise Ratio

These Single carrier frequency division mul- tiple access (SC-FDMA) has very low power consump- tion at the sender’s side, and it is the access scheme used for the uplink in long-term evolution (LTE). The objective of this work is to explore the error proba- bility of SC-FDMA system under sub-carrier mapping (SM) in heavily faded areas where the signal-to-noise ratios (SNRs) are very low. Wireless environment with heavily faded areas includes military radio systems; di- rect sequence spread spectrum system (DS-SS), global positioning system (GPS) etc. The localized FDMA (LFDMA) and distributed FDMA (DFDMA) are used to compare the performances of SC-FDMA in heavily faded areas. In heavily faded area with negative signal- to-noise ratio (SNR), the SC-FDMA system is imple- mented using modulation and encoding methods to re- ceive a very weak signal. Here, binary phase shift key- ing (BPSK), quadrature phase shift keying (QPSK), 16-PSK, quadrature amplitude modulation (QAM) and 16-QAM modulation techniques are used to calculate the bit error rate (BER) performances. The results show the BER performances of SC-FDMA using map- ping schemes for different channels, like, AWGN chan- nel, Rayleigh channel, COST207TU, and COST207RA channel models for heavily faded areas. In AWGN channel, BER at -15dB is about 10 times more than BER at 15dB. The COST207 model shows that the BER is less in typical urban (TU) area compared to the rural area (RA).The performance of BPSK modu- lation in SC-FDMA system is better in heavily faded areas than other modulation schemes

Performance Comparison of Optimization Methods for Flat-Top Sector Beamforming in a Cellular Network, Journal of Telecommunications and Information Technology, 2022, nr 3

The flat-top radiation pattern is necessary to form an appropriate beam in a sectored cellular network and to pro vide users with best quality services. The flat-top pattern offers sufficient power and allows to minimize spillover of signal to adjacent sectors. The flat-top sector beam pattern is relied upon In sectored cellular networks, in multiple-input multiple-output (MIMO) systems and ensures a nearly constant gain in the desired cellular sector. This paper presents a comparison of such optimization techniques as real-coded genetic algorithm (RGA) and particle swarm optimization (PSO), used in cellular networks in order to achieve optimum flat-top sector patterns. The individual parameters of flat-top sector beams, such as cellular coverage, ripples in the flat-top beam, spillover of radiation to the adjacent sectors and side lobe level (SLL) are investigated through optimization performed for 40◦ and 60◦ sectors. These parameters are used to compare the performance of the optimized RGA and PSO algorithms. Overall, PSO outperforms the RGA algorithm

Design of a Microstrip Filtering Antenna for 4G and 5G Wireless Networks, Journal of Telecommunications and Information Technology, 2023, nr 2

The filtering antenna provides both radiation and filtering features and is an important component for the RF front-end of wireless devices. The main function of a filtering antenna is to reject out-of-band signals, thus reducing the interference from adjacent channels. The aim of the present work is to design a 2.6 GHz microstrip filtering antenna for 4G and 5G global mobile services. The filtering antenna is designed using a hairpin bandpass filter integrated with an elliptical microstrip aerial. Good impedance matching is obtained by using appropriate dimensions of the hairpin bandpass filter. The 10 dB return loss bandwidth of the filtering antenna is approx. 5.7%, with the maximum gain for the elliptical filtering antenna of approx. 2.2 dB. Good agreements between the measured and simulated results are obtained for the proposed filtering antenna and the bandwidth covers almost the entire 2.6 GHz band

Optimization of Spectrum Sensing Parameters in Cognitive Radio Using Adaptive Genetic Algorithm, Journal of Telecommunications and Information Technology, 2017, nr 1

Quality of service parameters of cognitive radio, like, bandwidth, throughput and spectral efficiency are optimized using adaptive and demand based genetic algorithm. Simulation results show that the proposed method gives better real life solution to the cognitive radio network than other known approach

ADAPTIVE BEAMFORMING IN SMART ANTENNA USINGTCHEBYSCHEFF DISTRIBUTION AND VARIANTS OF LEAST MEAN SQUARE ALGORITHM

Tchebyscheff distribution is used for adaptive beam formation for smart antenna combined with different variants of least mean square (LMS) algorithm. Performances for accuracies of generated main beam direction and null direction and also side lobe level (SLL) are obtained using these hybrid algorithms. Tchebyscheff distribution with LMS (TDLMS), Tchebyscheff distribution with normalised LMS (TDNLMS) and Tchebyscheff distribution with sign LMS (TDSLMS) are used for adaptive beam generation and results are compared. Results show that using these hybrid algorithms low side lobe level can be obtained

Performance Comparison of Optimization Methods for Flat-Top Sector Beamforming in a Cellular Network

The flat-top radiation pattern is necessary to form an appropriate beam in a sectored cellular network and to pro vide users with best quality services. The flat-top pattern offers sufficient power and allows to minimize spillover of signal to adjacent sectors. The flat-top sector beam pattern is relied upon In sectored cellular networks, in multiple-input multiple-output (MIMO) systems and ensures a nearly constant gain in the desired cellular sector. This paper presents a comparison of such optimization techniques as real-coded genetic algorithm (RGA) and particle swarm optimization (PSO), used in cellular networks in order to achieve optimum flat-top sector patterns. The individual parameters of flat-top sector beams, such as cellular coverage, ripples in the flat-top beam, spillover of radiation to the adjacent sectors and side lobe level (SLL) are investigated through optimization performed for 40◦ and 60◦ sectors. These parameters are used to compare the performance of the optimized RGA and PSO algorithms. Overall, PSO outperforms the RGA algorithm