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Quantization and Waveform Coders
Published in Randy Goldberg, Lance Riek, A Practical Handbook of Speech Coders, 2019
The formula for μ-law companding is: () c(x)=xmaxloge(1+μ|x|/xmax)loge(1+μ)(sgn)(x);μ≥0
D/A and A/D Converters
Published in Jerry C. Whitaker, Microelectronics, 2018
PCM is a technique where an analog signal is sampled, quantized, and then encoded as a digital word. The PCM IC can include successive approximation techniques or other techniques to accomplish the PCM encoding. In addition, the PCM codec may employ nonlinear data compression techniques, such as companding, if it is necessary to minimize the number of bits in the output digital code. Companding is a logarithmic technique used to compress a code to fewer bits before transmission. The inverse logarithmic function is then used to expand the code to its original number of bits before converting it to the analog signal. Companding is typically used in telecommunications transmission systems to minimize data transmission rates without degrading the resolution of low-amplitude signals. Two standardized companding techniques are used extensively: A-law and μ-law. The A-law companding is used in Europe, whereas the μ-law is used predominantly in the United States and Japan. Linear PCM conversion is used in high-fidelity audio systems to preserve the integrity of the audio signal throughout the entire analog range.
Basics of Electrical Communication Systems
Published in P. S. Neelakanta, ATM Telecommunications, 2018
The companding on voice signals facilitate a relatively constant S/Nq ratio performance over a wide dynamic range. The parameter μ defines the amount of compression to achieve a given performance. For the same intended dynamic range, A-law companding has a slightly flatter S/Nq ratio than the μ-law.
An efficient and improved PTS algorithm for PAPR reduction in OFDM system
Published in International Journal of Electronics, 2022
Prabal Gupta, H. Pal Thethi, Ajay Tomer
In (Thafasal Ijyas & Al-Rayif, 2019), authors derived a new, low complexity PAPR reduction and demodulation method. In addition to this, authors also established a novel time domain technique for sending side information. In (Liang, 2019), authors proposed an adaptive threshold value for evaluation of characteristic of input signals. This research paper selected optimal generation of phase mechanism to generate phase sequences. Through this projected technique, generation of phases were recognized in according to reed-muller codes, henceforth obtaining systematic structures which normal creation method lacked. In (Gupta et al., 2019), authors projected an algorithm which was based upon SLM and DCT matrix. In (Gupta & Thethi, 2020), authors projected SLM method with pseudo-random phase sequences and also μ-law companding. In (Gupta et al., 2015), authors proposed PTS with bose chaudhuri hocquenghem code (BCH). In (Bharati & Podder, 2020), authors demonstrated a system which was an arrangement of two different techniques such as SLM and Clipping. Simulation results specified that offered method acquired appropriate reduction of PAPR with small complexity. The PAPR reduction was also analyzed for several subcarriers and compared with existing methods. In (Sarowa et al., 2020), authors demonstrated comparative study of conventional and current PAPR reduction techniques in wavelet-based OFDM to create excellent system. The optimization of PAPR was obtained through integration of clipping, companding and wavelet. Authors also analyzed several modulation methods for the projected hybrid system. In (Kotade et al., 2021), authors proposed tail biting convolution coding (TBCC) method using bit by bit (BYB) and look up table (LUT) approaches on free scale starcore sc140 based platform of DSP and projected an excellent algorithm by comparing memory requirements and machine cycles. Authors also analyzed TBCC for PAPR to get overall results.