Capacity-achieving CPM schemes

The pragmatic approach to coded continuous-phase modulation (CPM) is proposed as a capacity-achieving low-complexity alternative to the serially-concatenated CPM (SC-CPM) coding scheme. In this paper, we first perform a selection of the best spectrally-efficient CPM modulations to be embedded into SC-CPM schemes. Then, we consider the pragmatic capacity (a.k.a. BICM capacity) of CPM modulations and optimize it through a careful design of the mapping between input bits and CPM waveforms. The so obtained schemes are cascaded with an outer serially-concatenated convolutional code to form a pragmatic coded-modulation system. The resulting schemes exhibit performance very close to the CPM capacity without requiring iterations between the outer decoder and the CPM demodulator. As a result, the receiver exhibits reduced complexity and increased flexibility due to the separation of the demodulation and decoding functions.Comment: Submitted to IEEE Transactions on Information Theor

An FPGA Design of High-Speed Adaptive Turbo Decoder for Broadband Wireless Communications

This thesis proposes an adaptive turbo decoding algorithm for high order modulation scheme combined with original design for a standard rate-1/2 turbo decoder for B/QPSK modulation. A transformation applied to the incoming I-channel and Q-channel symbols allows the use of an off-the-shelf B/QPSK turbo decoder without any modifications. Adaptive turbo decoder processes the received symbols recursively to improve the performance. As the number of iterations increases, the execution time and power consumption also increase as well. To reduce the latency and power consumption, this thesis employs the combination of the radix-4, dual-path processing, parallel decoding, and early-stop algorithms. This thesis implemented the proposed scheme on a field-programmable gate array (FPGA) and compared its decoding speed with that of a conventional decoder. From the result of implementation, it was found that the decoding speed of proposed adaptive decoding is faster than that of conventional scheme by 6.4 times under the following conditions : N=212, iteration=3, 8-states, 3 iterations, and 8PSK modulation scheme.Chapter I. Introduction = 1 Chapter II. Adaptive Turbo Decoding Algorithm = 4 2.1 Mapping of bits to signal = 7 2.2 Coset Symbol Transformer(CST) = 8 2.3 Phase Sector Quantizer(PSQ) = 10 2.4 Simulation Results = 13 Chapter III. High Speed Turbo Decoder Algorithm = 15 3.1 Radix-4 Algorithm = 16 3.2 Dual-Path Processing Algorithm = 18 3.3 Parallel Decoding Algorithm = 21 3.4 Early Stop Algorithm = 22 3.5 Simulation Results = 23 Chapter IV. Design of the Adaptive High-Speed Turbo Decoder = 24 4.1 The Adaptive High-Speed Turbo Decoder Structure = 25 4.2 The Optimum Quantized Bits of the Adaptive Turbo Decoder = 28 4.3 FPGA Implementation = 29 Chapter V. Conclusion = 33 References = 3

Linearisation, error correction coding and equalisation for multi-level modulation schemes

University of Technology, Sydney. Faculty of Engineering.Orthogonal frequency division multiplexing (OFDM) has been standardised for digital audio broadcasting (DAB), digital video broadcasting (DVB) and wireless local area networks (WLAN). OFDM systems are capable of effectively coping with frequency- selective fading without using complex equalisation structures. The modulation and demodulation processes using fast fourier transform (FFT) and its inverse (IFFT) can be implemented very efficiently. More recently, multicarrier code division multiple access (MC-CDMA) based on the combination of OFDM and conventional CDMA has received growing attention in the field of wireless personal communication and digital multimedia broadcasting. It can cope with channel frequency selectivity due to its own capabilities of overcoming the asynchronous nature of multimedia data traffic and higher capacity over conventional multiple access techniques. On the other hand, multicarrier modulation schemes are based on the transmission of a given set of signals on large numbers of orthogonal subcarriers. Due to the fact that the multicarrier modulated (MCM) signal is a superposition of many amplitude modulated sinusoids, its probability density function is nearly Gaussian. Therefore, the MCM signal is characterised by a very high peak-to-average power ratio (PAPR). As a result of the high PAPR, the MCM signal is severely distorted when a nonlinear high power amplifier (HPA) is employed to obtain sufficient transmitting power. This is very common in most communication systems, and decreases the performance significantly. The simplest way to avoid the nonlinear distortion is substantial output backoff (OBO) operating in the linear region of the HPA. However, because of the high OBO, the peak transmit power has to be decreased. For this reason, many linearisation techniques have been proposed to compensate for the nonlinearity without applying high OBO. The predistortion techniques have been known and studied as one of the most promising means to solve the problem. In this thesis, an improved memory mapping predistortion technique devised to reduce the large computational complexity of a fixed point iterative (FPI) predistorter is proposed, suitable especially for multicarrier modulation schemes. The proposed memory mapping predistortion technique is further extended to compensate for nonlinear distortion with memory caused by a shaping linear filter. The case of varying HPA characteristics is also considered by using an adaptive memory mapping predistorter which updates the lookup table (LUT) and counteracts these variations. Finally, an amplitude memory mapping predistorter is presented to reduce the LUT size. Channel coding techniques have been widely used as an effective solution against channel fading in wireless environments. Amongst these, particular attention has been paid to turbo codes due to their performance being close to the Shannon limit. In-depth study and evaluation of turbo coding has been carried out for constant envelope signaling systems such as BPSK, QPSK and M-ary PSK. In this thesis, the performance of TTCM-OFDM systems with high-order modulation schemes, e.g. 16-QAM and 64-QAM, is investigated and compared with conventional channel coding schemes such as Reed-Solomon and convolutional coding. The analysis is performed in terms of spectral efficiency over a multipath fading channel and in presence of an HPA. Maximum a-priori probability (MAP), soft output Viterbi algorithm (SOVA) and pragmatic algorithms are compared for non-binary turbo decoding with these systems. For this setup, iterative multiuser detection in TTCM/MC-CDMA systems with M-QAM is introduced and investigated, adopting a set of random codes to decrease the PAPR. As another application of TTCM, the performance of multicode CDMA systems with TTCM for outer coding over multipath fading channels is investigated

Combined source-channel coding for a power and bandwidth constrained noisy channel

This thesis proposes a framework for combined source-channel coding under power and bandwidth constrained noisy channel. The framework is then applied to progressive image coding transmission using constant envelope M-ary Phase Shift Key (MPSK) signaling over an Additive White Gaussian Channel (AWGN) channel. First the framework for uncoded MPSK signaling is developed. Then, its extended to include coded modulation using Trellis Coded Modulation (TCM) for MPSK signaling. Simulation results show that coded MPSK signaling performs 3.1 to 5.2 dB better than uncoded MPSK signaling depending on the constellation size. Finally, an adaptive TCM system is presented for practical implementation of the proposed scheme, which outperforms uncoded MPSK system over all signal to noise ratio (Es/No) ranges for various MPSK modulation formats. In the second part of this thesis, the performance of the scheme is investigated from the channel capacity point of view. Using powerful channel codes like Turbo and Low Density Parity Check (LDPC) codes, the combined source-channel coding scheme is shown to be within 1 dB of the performance limit with MPSK channel signaling

Capacity -based parameter optimization of bandwidth constrained CPM

Continuous phase modulation (CPM) is an attractive modulation choice for bandwidth limited systems due to its small side lobes, fast spectral decay and the ability to be noncoherently detected. Furthermore, the constant envelope property of CPM permits highly power efficient amplification. The design of bit-interleaved coded continuous phase modulation is characterized by the code rate, modulation order, modulation index, and pulse shape. This dissertation outlines a methodology for determining the optimal values of these parameters under bandwidth and receiver complexity constraints. The cost function used to drive the optimization is the information-theoretic minimum ratio of energy-per-bit to noise-spectral density found by evaluating the constrained channel capacity. The capacity can be reliably estimated using Monte Carlo integration. A search for optimal parameters is conducted over a range of coded CPM parameters, bandwidth efficiencies, and channels. Results are presented for a system employing a trellis-based coherent detector. To constrain complexity and allow any modulation index to be considered, a soft output differential phase detector has also been developed.;Building upon the capacity results, extrinsic information transfer (EXIT) charts are used to analyze a system that iterates between demodulation and decoding. Convergence thresholds are determined for the iterative system for different outer convolutional codes, alphabet sizes, modulation indices and constellation mappings. These are used to identify the code and modulation parameters with the best energy efficiency at different spectral efficiencies for the AWGN channel. Finally, bit error rate curves are presented to corroborate the capacity and EXIT chart designs

Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping

In this paper, we provide for the first time a systematic comparison of distribution matching (DM) and sphere shaping (SpSh) algorithms for short blocklength probabilistic amplitude shaping. For asymptotically large blocklengths, constant composition distribution matching (CCDM) is known to generate the target capacity-achieving distribution. As the blocklength decreases, however, the resulting rate loss diminishes the efficiency of CCDM. We claim that for such short blocklengths and over the additive white Gaussian channel (AWGN), the objective of shaping should be reformulated as obtaining the most energy-efficient signal space for a given rate (rather than matching distributions). In light of this interpretation, multiset-partition DM (MPDM), enumerative sphere shaping (ESS) and shell mapping (SM), are reviewed as energy-efficient shaping techniques. Numerical results show that MPDM and SpSh have smaller rate losses than CCDM. SpSh--whose sole objective is to maximize the energy efficiency--is shown to have the minimum rate loss amongst all. We provide simulation results of the end-to-end decoding performance showing that up to 1 dB improvement in power efficiency over uniform signaling can be obtained with MPDM and SpSh at blocklengths around 200. Finally, we present a discussion on the complexity of these algorithms from the perspective of latency, storage and computations.Comment: 18 pages, 10 figure