Development of Nonlinear Filtering Algorithms of Digital Half-Tone Images

This chapter is devoted to solving the problem of algorithms and structures investigations for Radio Receiver Devices (RRD) with the aim of the nonlinear filtering of Digital Half-Tone Images (DHTI) representing the discrete-time and discrete-value random Markovian process with a number of states greater than two. At that, it is assumed that each value of the DHTI element is represented by the binary g-bit number, whose bits are transmitted via digital communication links in the presence of Additive White Gaussian Noise (AWGN). The authors present the qualitative analysis of the optimal DHTI filtering algorithm. The noise immunity of the optimal radio receiver device for the DHTI filtering with varying quantization and dimension levels is investigated

Two novel nonlinear companding schemes with iterative receiver to reduce PAPR in multi-carrier modulation systems

Companding transform is an efficient and simple method to reduce the Peak-to-Average Power Ratio (PAPR) for Multi-Carrier Modulation (MCM) systems. But if the MCM signal is only simply operated by inverse companding transform at the receiver, the resultant spectrum may exhibit severe in-band and out-of-band radiation of the distortion components, and considerable peak regrowth by excessive channel noises etc. In order to prevent these problems from occurring, in this paper, two novel nonlinear companding schemes with a iterative receiver are proposed to reduce the PAPR. By transforming the amplitude or power of the original MCM signals into uniform distributed signals, the novel schemes can effectively reduce PAPR for different modulation formats and sub-carrier sizes. Despite moderate complexity increasing at the receiver, but it is especially suitable to be combined with iterative channel estimation. Computer simulation results show that the proposed schemes can offer good system performances without any bandwidth expansion

Flexible Multi-Group Single-Carrier Modulation: Optimal Subcarrier Grouping and Rate Maximization

Orthogonal frequency division multiplexing (OFDM) and single-carrier frequency domain equalization (SC-FDE) are two commonly adopted modulation schemes for frequency-selective channels. Compared to SC-FDE, OFDM generally achieves higher data rate, but at the cost of higher transmit signal peak-to-average power ratio (PAPR) that leads to lower power amplifier efficiency. This paper proposes a new modulation scheme, called flexible multi-group single-carrier (FMG-SC), which encapsulates both OFDM and SC-FDE as special cases, thus achieving more flexible rate-PAPR trade-offs between them. Specifically, a set of frequency subcarriers are flexibly divided into orthogonal groups based on their channel gains, and SC-FDE is applied over each of the groups to send different data streams in parallel. We aim to maximize the achievable sum-rate of all groups by optimizing the subcarrier-group mapping. We propose two low-complexity subcarrier grouping methods and show via simulation that they perform very close to the optimal grouping by exhaustive search. Simulation results also show the effectiveness of the proposed FMG-SC modulation scheme with optimized subcarrier grouping in improving the rate-PAPR trade-off over conventional OFDM and SC-FDE.Comment: Submitted for possible conference publicatio

Channel Estimation and Optimal Pilot Signals for Universal Filtered Multi-Carrier (UFMC) Systems

We propose channel estimation algorithms and pilot signal optimization for the universal filtered multi-carrier (UFMC) system based on the comb-type pilot pattern. By considering the least square linear interpolation (LSLI), discrete Fourier transform (DFT), minimum mean square error (MMSE) and relaxed MMSE (RMMSE) channel estimators, we formulate the pilot signals optimization problem by minimizing the estimation MSE subject to the power constraint on pilot tones. The closed-form optimal solutions and minimum MSE are derived for LSLI, DFT, MMSE and RMMSE estimators