To ensure reliable communications,(an algorithm has been built for bit error detection and correction). To achieve this
goal, special codeword combinations and their related parity codes are used as powerful detection and correction codes.
All codeword combinations are divided into four main groups, where each code in a group has a common parity code. In
this paper, we used the distance feature between special selected codeword combinations and unique combinations from
a fixed set to improve the BER in digital communications systems. The results of using such algorithm show that 100%
correction of two errors and 66% of three errors. The probability of detection is very high and up to 8 errors in different
positions. All correction and detection processes are achieved with minimum number of transmitted bits representing 4-
ary PAM symbols with compression ratio equals to 76% comparing to traditional distance parity check codes.
Proc. SPIE. 7745, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010
KEYWORDS: Signal to noise ratio, Transmitters, Modulation, Resistance, Receivers, Telecommunications, Non-line-of-sight propagation, Orthogonal frequency division multiplexing, Signal detection, Binary data
In this work we compare an orthogonal frequency division multiplexing (OFDM) single user through multi carrier system with Direct Sequence Spread Spectrum (DS- SS) in the presence of multipath fading and AWGN. A closed-form of mathematical expressions for both receivers is derived to calculate the symbol error probability. The OFDM system simulator is an IEEE 802.15.3a proposal, dated 15 September 2003 (Doc: IEEE P802.15-03/268r1). Conventional matched filter (MF) is proposed in DS-SS system. UWB - Multiband OFDM has an acceptable BER performance, but in a multipath noisy channel the bit error rate is very high. This Paper presents the Barker code as a coding technique to increase the BER performance depending on the auto and cross correlation detections.
Compression of speech signals is very important in signal processing, data transmission and data storage. Therefore in
this paper a new method for compression speech signals that have a significant number of zeros and ones after encoding
has been proposed and the proposed name for this method is Zeros-Ones Position Method (ZOPM). Also a new
statistical evaluation method is used to evaluate the reconstructed signal and compare it with the original one. Results
obtained from the simulation program show that in speech signals containing 60% of silent intervals can give 2.3
compression ratio (CR) due to ZOPM. In this paper the proposed ZOPM method is compared with Huffman encoding for signals with enough large numbers of zeros.
Zero-Compression Method (ZCM) is a simple and effective algorithm that can be used to compress the digital data
which consists of a significant numbers of zeros. The method has the ability to encode and decode the data with high
processing speed and it has the ability to recover the stored data with minimum error and minimum storage area. On the
other hand, the ZCM may have a wide practical value in storing data extracted from ECG signals. The method is
implemented for various types of signals such as textual data, wavelet subsignals, randomly generated signals and speech
signals. In this paper the coding and decoding algorithm is presented.