A new bound and algorithm for star 16-QAM carrier phase estimation

Copyright © 2003 IEEEThe true Cramer-Rao lower bound (CRLB) is derived and evaluated for the estimation of carrier phase of Star 16-quadrature amplitude modulation (QAM) and can be simply applied to carrier frequency estimation. Different geometries are investigated by varying the ring ratio (RR). For signal-to-noise ratios (SNRs) between 6-15 dB, the CRLB with RR=3 is lower than that of Square 16-QAM. A modified phase estimator is presented, which closely follows the new CRLB. Investigation of symbol error performance in short packet length reveals Star 16-QAM to be superior to Square 16-QAM for SNR<13 dB, which is a reasonable operating range for a coded system. Although Square 16-QAM and Star RR=1.8 are optimum for a perfect receiver, when the effect of phase estimation is considered, we find Star RR=3 to be better for SNR below 10 dB.Feng Rice, Mark Rice, and Bill Cowle

Design guidelines for spatial modulation

A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants

Asymptotic Performance of the Pth Power-Law Phase Estimator

An expression for the true variance of the Pth powerlaw phase estimator, as the number of samples approaches infinity, is given. This expression is an extension to the linear approximation of Moeneclaey and de Jonghe [1] which is known to be inadequate in some practical systems. Our new expression covers general 2π/P-rotationally symmetric constellations that include those of PAM, QAM, PSK, Star M-QAM, MR-DPSK, and others. This expression also generalizes the known expressions for QAM and PSK. Additionally, our expression reduces to the Cramer-Rao bound given by Steendam and Moeneclaey [9], as SNR goes to zero. Monte Carlo simulations provide experimental verification of the theoretical expression for various constellations

Existence of codes with constant PMEPR and related design

Recently, several coding methods have been proposed to reduce the high peak-to-mean envelope ratio (PMEPR) of multicarrier signals. It has also been shown that with probability one, the PMEPR of any random codeword chosen from a symmetric quadrature amplitude modulation/phase shift keying (QAM/PSK) constellation is logn for large n, where n is the number of subcarriers. Therefore, the question is how much reduction beyond logn can one asymptotically achieve with coding, and what is the price in terms of the rate loss? In this paper, by optimally choosing the sign of each subcarrier, we prove the existence of q-ary codes of constant PMEPR for sufficiently large n and with a rate loss of at most log/sub q/2. We also obtain a Varsharmov-Gilbert-type upper bound on the rate of a code, given its minimum Hamming distance with constant PMEPR, for large n. Since ours is an existence result, we also study the problem of designing signs for PMEPR reduction. Motivated by a derandomization algorithm suggested by Spencer, we propose a deterministic and efficient algorithm to design signs such that the PMEPR of the resulting codeword is less than clogn for any n, where c is a constant independent of n. For symmetric q-ary constellations, this algorithm constructs a code with rate 1-log/sub q/2 and with PMEPR of clogn with simple encoding and decoding. Simulation results for our algorithm are presented

Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems

Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms

Chapter Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems

Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms

Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems

Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms

Synchronization in all-digital QAM receivers

The recent advance in Field Programmable Gate Array (FPGA) technology has been largely embraced by the communication industry, which views this technology as an effective and economical alternative to the design of Application Specific Integrated Circuits (ASICs). The primary reasons for switching to FPGAs are lower development and non-recurring engineering costs, the flexibility to design to a preliminary standard and adapt the design as the standard evolves, as well as the option of performing software updates in the field. A sector with strong interest in FPGAs is the coaxial cable TV/Internet distribution industry. The creation of soft preliminary standards by the standards organization governing the industry has been the main catalyst for the massive adoption of FPGAs by small to medium size companies, which see this technology as an opportunity to compete in this open market. Both the circuit speed and the economy of FPGA technology depend upon using algorithms that map efficiently into its fabric. Often it is prudent to sacrifice performance to improve either clock speed or economy when developing with FPGAs. The purpose of this research is to both revise and devise synchronization algorithms / structures for cable digital receivers that are to be implemented in FPGA. The main communication scheme used by the coaxial cable distribution industry is digital Quadrature Amplitude Modulation (QAM). The problem of synchronizing to the QAM signal in the receiver is not a new topic and several synchronization-related circuits, which were devised with ASICs implementation in mind, can be found in the open literature. Of interest in this thesis is the non-data-aided digital timing synchronizer that was proposed by D'Andrea to recover timing with no knowledge of the transmitted data. Accurate timing estimation was achieved by reshaping the received signal with a prefilter prior to estimating the timing. A problem with D'Andrea's synchronizer is that the prefilter for reshaping the signal is a relatively long Finite Impulse Response (FIR) filter, whose implementation requires a large number of multipliers. This may not have been an issue with ASICs in as much as the number of hardwired multipliers on a chip is not limited as it is in an FPGA chip. One contribution in this research is to propose an alternative to D'Andrea's synchronizer by replacing the long FIR filter with two single-pole Infinite Impulse Response (IIR) filters that are directly placed inside the timing recovery loop. This novel architecture, which drastically reduces the number of multipliers, is well suited for FPGA implementation. Non-data-aided feedforward synchronizers, which use the same prefilter as D'Andrea's synchronizer, have been receiving significant attention in recent years. Detailed performance analysis for these synchronizers can be found in the open literature. These synchronizers have the advantage of using a feedfordward structure rather than a feedback structure, as it is the case in D'Andrea's synchronizer, to estimate the timing. While D'Andrea's synchronizer has an advantage in performance over a non-data-aided feedforward synchronizer, this has not been reported in the literature. In this thesis a second contribution consists of thoroughly analyzing the steady state timing jitter in D'Andrea synchronizer by deriving a closed-form expression for the noise power spectrum and a simple equation to estimate the timing jitter variance. A third contribution is a novel low-complexity and fast acquisition coherent detector for the detection of Quadrature Phase Shift Keying (QPSK) (i.e., 4-QAM) symbols. This detector performs carrier phase synchronization much faster than a conventional coherent detector. The acquisition time is comparable to that of a differential detector. The fast acquisition comes at the expense of phase jitter, and the end result is a 1 dB performance loss over theoretical coherent detection. This detector can be used in place of the differential detector with no economic penalty. Doing so yields a performance advantage of about 2 dB over differential detection