Cenk Albayrak

Reduced-Complexity Decoding of LT Codes

In this paper, the belief propagation (BP) based approximation methods for low-density parity-check codes are adapted to the Luby transform soft decoder structure in order to reduce its computational complexity. Moreover, the log-likelihood ratio based adaptive demodulation algorithm is combined with the BP and BP-based algorithms to further reduce the computational complexities and optimum key parameters are determined for normalized min-sum and offset min-sum algorithms. The bit error rate performances of the algorithms over the binary input additive white Gaussian noise channel are obtained by both theoretically and simulations. For theoretical analysis, the Monte-Carlo based density evolution method is used. In addition, computational complexity analyzes of methods are presented. Results show that the computational complexity can be reduced significantly by using combined methods which cost limited signal to noise ratio loss.

BP-based approximation methods for rateless codes

In this letter, belief propagation (BP) based approximation methods for low density parity check (LDPC) codes are adapted to the Luby transform (LT) soft decoder structure in order to reduce its computational complexity. The bit error rate (BER) performances of the algorithms over the binary input additive white Gaussian noise (BIAWGN) channel are obtained by both theoretically and simulations. For theoretical analysis, the Monte-Carlo density evolution (MC-DE) method is used. In addition, computational complexity analyzes of methods are presented. Results show that the computational complexity can be significantly decreased with a limited performance loss cost.

Rate adaptive system for visible light communications

Visible light communications (VLC) use light emitting diodes (LEDs) for both illumination and data transmission. In this work, we propose a rate adaptive system based on Raptor codes for VLC system. We consider realistic channel by using a model room with multiple LED armatures. Chosen LEDs are commercially available (Cree Xlamp ML-C). It is assumed that LEDs simultaneously transmit same data and the VLC receiver moves around in the room. Simulation results show that proposed rate adaptive system gives seamless rate adaptation and significantly improves the spectral efficiency.

Low-Complexity Early Termination Method for Rateless Soft Decoder

We propose a new early termination method (ETM) with low computational complexity for Luby transform belief propagation (BP) decoder. The proposed method, which we call least reliable messages (LRM) ETM, observes only sign alterations of a small cluster in log-likelihood ratio messages passing between nodes in BP decoder. Simulation results and complexity analyzes show that LRM ETM has quite low computational complexity and small average iteration amounts without any performance degradation compared with conventional ETMs in literature. The method can be applied to code families which can be decoded by BP such as low density parity check codes, polar codes, and Raptor codes.

Reduced-complexity decoding algorithms of Raptor codes

In this paper, the belief propagation (BP) based approximation methods which are introduced for low density parity check (LDPC) codes in literature are adapted to the Raptor decoder structure in order to reduce its computational complexity. The bit error rate (BER) performances of the algorithms over the additive white Gaussian noise (AWGN) channel are obtained by both theoretical works and simulations. The Monte-Carlo based density evolution (MC-DE) method is used for theoretical analysis. In addition to this, computational complexity analyses of the considered methods are presented. Results show that the computational complexity can be significantly decreased with a limited performance loss cost.

Low complexity, losless ECG data compression algorthims for Wireless Sensor Network

Wireless sensor networks, with their low cost, small size, low energy consumption expanding their use in home automation and environmental monitoring systems. With the help of these benefits there has been an increasing demand on wireless patient monitoring systems recently. One of the important parts of patient monitoring systems is ECG measurement which requires high resolution sampling and high data rates. That leads a ceartain need of a low loss and low complexity data compression for systems like Zigbee and Bluetooth which can not provide high data rates and high computing power. In this study two low complexity lossless and low-loss data compression algorithms are presented being able to use in wireless sensor networks. First algorithm implements a shift values for the greater inputs with a pre-selected shifting steps to lower value. The second method implements a low-loss logaritmic scaling to samples that expressed by more than a byte for reducing the content to 1 byte like first algortihm. Thus, a significant data reduction has been made for a low data rate wireless communications, i.e. Bluetooth and ZigBee, which helps to reduce the latency. Proposed techniques keep the sensitive portion of the data untouched, as in ECG signals, and can be implemented by a very low profile microprocessor.