Enhanced Performance of Narrowband Power Line Communications using Recursive Least Squares Filter

Noises presented in a power line communication channel tend to distort the message signals, leading towards the reception of erroneous data at the receiver end. Mitigation of noise existent in power line has always been of prime interest and helped to improve the BER performance of a communication system as it accounts for efficient data transmission. In this work, adaptive filters based on the Recursive Least Squares (RLS) algorithm and Least Mean Square (LMS) algorithms have been implemented in Simulink to investigate the effectiveness of an Adaptive Noise Canceller for the mitigation of Gaussian and Impulsive Noises present in a narrowband power line channel model. The performance of the RLS algorithm against that of the LMS algorithm was compared in adaptive filtering for the same channel conditions. The error performances of BPSK and FSK schemes for the channel model in a generic digital communication system were also compared in Simulink. Furthermore, the use of convolutional codes and interleaving for the correction of random bit errors and for condensing the negative effect of burst errors respectively were investigated during the transmission of data signals over the generic communication system designed in Simulink. From the findings of the study, it has been concluded that the RLS algorithm proves to be more effective than the LMS algorithm. For a BER of 10-5, a coding gain of less than 10 dB is achievable for both Binary Phase Shift Keying and Binary Frequency Shift Keying. With the addition of convolutional coding and convolutional interleaving, the error performance of the channel is further improved, rendering the power line channel more reliable for data communication

Modeling Of Power Line Communication Channel For Automatic Meter Reading System With LDPC Codes

In this era of modernization, one of the promising emerging technologies is Power Line Communication (PLC) system. In previous research fields, modeling of PLC channel, mostly for indoor applications has been studied. However, the need to study that for outdoor applications, such as the Automatic Meter Reading (AMR) systems is also vital. Moreover, standardization bodies have considered the use of LDPC codes restricted for indoor systems. Thus, in this paper, not only we model the PLC channel based on AMR applications, but also, we apply LDPC coding scheme to the system. To accomplish the objectives, firstly, we model the PLC-AMR channel, which includes multipath phenomenon. Additionally, PLC noise, usually occurring in the channel, is modeled. The modulation technique applied is BPSK and the performance of the system with varying load impedances is compared. The coded system consists of irregular LDPC codes, with two different constructions of the Parity-Check matrix, namely that by Radford Neal and reduced size of DVBS2. The performances of respective systems are then compared. Using LDPC by Radford Neal, the performances are analyzed with varied code rates

Adaptive Combined Source and Channel Decoding with Modulation for Rayleigh Fading Channels

In this paper, an adaptive system employing combined source and channel decoding with modulation is  proposed for slow Rayleigh fading channels. Huffman code is used as the source code and Convolutional code is  used for error control. The adaptive scheme employs a family of Convolutional codes of different rates and  Multiple Phase Shift Keying (MPSK) modulation schemes according to the states of the channel. It also uses a channel estimator to select the most appropriate codulation scheme. Simulation results show that the adaptive scheme gives significant improvement in the BER and throughput performance as compared to fixed error codes