Decision-directed Algorithm Research Articles

OF-FSE: An Efficient Adaptive Equalization for QAM-Based UAV Modulation Systems

Quadrature amplitude modulation (QAM) is one of the essential components of unmanned 1 aerial vehicle (UAV) communications. However, the output signal accuracy of QAM deteriorates dramatically and even collapses in the case of UAVs in a harsh channel environment. This is due to the fractionally spaced equalization based on the multi-modulus blind equalization algorithm being implemented prior to carrier synchronization in QAM-based UAV modulation systems. The carrier frequency offset from the harsh channel signal thus contributes to the significantly degraded performance of MMA by suffering the fractionally spaced equalization. Therefore, in this paper, a novel offset feedback fractionally spaced equalization architecture for UAVs to eliminate the carrier frequency offset is first proposed. In this architecture, the carrier frequency offset allows estimated and incorporation into the input signal of fractionally spaced equalization to compensate for the offset. Moreover, a new multi-modulus decision-directed algorithm is presented for the novel architecture to improve the received signal accuracy of UAVs further. It enables adaptive optimization of the convergence process in accordance with the dynamic UAV communication environment employing the multi-modulus blind equalization algorithm and decision-directed blind equalization algorithm (MDD). Simulation results demonstrate the effectiveness of the OF-FSE framework in enabling the QAM-based UAV modulation systems operation in harsh channel scenarios. Moreover, the performance of the presented new MDD algorithm compared with baseline approaches is also confirmed.

Non-Data-Aided SNR Estimation for Bandlimited Optical Intensity Channels

Powerful and reliable estimation of transmission parameters is an indispensable task in each receiver unit-not only for radio frequency, but also for optical wireless communication systems. In this context, the signal-to-noise ratio (SNR) plays an eminent role, especially for adaptive scenarios. Assuming a bandlimited optical intensity channel, which requires a unipolar waveform design, an algorithm for SNR estimation is developed in this paper, which requires no knowledge of the transmitted data. This non-data-aided approach benefits to a great extent from the fact that very long observation windows of payload symbols might be used for the estimation process to increase the accuracy of the result; this is in striking contrast to a data-aided approach based on pilot symbols reducing the spectral efficiency of a communication link. Since maximum likelihood, moment-based or decision-directed algorithms are not considered for complexity and performance reasons, an expectation-maximization solution is introduced whose error performance is close to the Cramer-Rao lower bound as the theoretical limit, which has been derived as well.

A double-DD blind equalizer for PolMux QAM optical coherent systems

In polarization-multiplexed (PolMux) coherent system, adaptive blind equalization is efficient in demultiplexing and mitigating inter-symbol interference (ISI). We propose a double decision-directed (double-DD) blind algorithm which combines the output of soft decision-directed (SDD) algorithm with that of the equalizer in variable step size decision-directed (VSS-DD) mode. In our scheme, two equalizers can softly switch when the mean-square error (MSE) is sufficiently low and it can achieve fast convergence rate and small steady MSE in steady state. By simulation in PolMux-16QAM/64QAM coherent systems, we show that the double-DD algorithm outperforms existing blind equalizers.

Iterative noncoherent block detection of coded MPSK for cooperative relay systems

Maximum likelihood (ML) noncoherent block detection techniques are investigated for block-coded MPSK modulation in cooperative decode-and-forward relay systems over slow fading channels. A decision-directed iterative Viterbi algorithm (IVA) is derived for a suboptimal ML noncoherent detection. Simulation results show that the IVA can approach the error performances of the exhaustive detection method but at a lower complexity.

오차 스케일링에 의해 블라인드 수렴 특성을 개선한 새로운 판정의거 등화

The Decision-directed (DD) algorithm is known to be not effective to initialize a blind equalizer in the channel conditions when the eye diagram of received signals is completely closed because it can not open the eye diagram enough. In this paper, we propose a new error to replace the error of the conventional DD algorithm. The new DD error is the conventional DD error scaled by the modulus of symbol decision, new DD algorithm using this error is effective to open the closed eye diagram in early stage of equalization unlike the conventional DD. The new DD algorithm appling the new error is showed excellent convergence characteristics as compared to the CMA widely used in blind initialization, particularly, is useful for equalization of signals having multimodulus. The performance of the new DD algorithm is verified through the simulation for the higher-order QAM signals. ※ 이 연구는 2014년도 광주대학교 대학 연구비의 지원을 받아 수행되었음. First Author : Dept. of Optical Commun. Eng., Gwangju Univ., knoh@gwangju.ac.kr, 종신회원 논문번호:KICS2015-01-008, Received January 12, 2015; Revised March 11, 2015; Accepted March 11, 2015 I. 서 론 고차 QAM(quadrature amplitude modulation) 신 호에 대한 블라인드 등화 시, 블라인드 초기화에 널리 사용되는 CMA(constant modulus algorithm)는 원 신호점 대신 일정 모듈러스(constant modulus)를 기준 신호(reference signal)로 사용하여 등화기의 수렴을 달성한다. 그러나 그 대가로 CMA는 정상상태 성능이 The Journal of Korean Institute of Communications and Information Sciences '15-03 Vol.40 No.03 420 k h n s n y + n ν

An Optimized Combination of Frequency Domain Adaptive Equalizers

In order to overcome the defects of the high computational loads and selecting the threshold of mean square error (MSE) for time domain decision-directed constant modulus blind equalization algorithm (DD+CMA), a frequency domain parallel decision multi-modulus blind equalization algorithm based on frequency domain MMA(FMMA) and frequency domain LMS (FLMS) algorithm is proposed. The proposed algorithm is composed of the FMMA and FLMS, and the FMMA and FLMS run automatically in soft switching parallel manner. In running process, it is not necessary to selecting the threshold of the MSE. Moreover, the computational loads can be reduced by circular convolution in the frequency domain signals instead of linear one of the time domain signals. Simulation results show that performance of the proposed algorithm outperforms the FLMS and the FMMA algorithm.

De-multiplexing based on complex ICA for mode group diversity multiplexing system

In order to mitigate the crosstalk in mode group diversity multiplexing (MGDM) system, the fixed-point complex ICA algorithm (T-CMN) based on negative entropy maximization is proposed to implement de-multiplexing in a 2 $$\times $$ 2 MGDM system in which two QAM signals are transmitted. The performance of this algorithm is compared with the DD-LMS (Decision-directed Least Mean Square Algorithm). The results indicate that the T-CMN algorithm separates the signals successfully and achieves a better de-multiplexing performance than DD-LMS.

Adaptive Blind Equalization of QAM Transmitted Constellations across Linear Band-Limited Channel

ISI (Intersymbol Interference) severely degrades the performance of high speed digital communication systems. A popular technique for countering ISI is Adaptive Equalization. Blind/Unsupervized equalization is one class of adaptive equalization where initial training of equalizer’s weights is not feasible. Godard’s Constant Modulus Algorithm (CMA) was the very first blind equalization algorithm that could be applied for two dimensional communication systems. It requires the transmitted signal’s statistics to perform equalization. Picchi & Prati modified the standard decision-directed algorithm and proposed a new algorithm by the name Stop-and-Go. Wei Rao by simply converting the equalizer’s output proposed a modified version of the CMA. This paper compares the performance of blind equalization algorithms: CMA, Stop-and-Go decisiondirected algorithm and Wei Rao’s modified constant modulus algorithm for 16 and 64-QAM constellations transmitted across a linear band-limited channel. Simulation results indicate impulse response of the cascade of transmission channel and equalizer (after convergence) is similar to that of ideal transmission channel‘s impulse response. The results also show that stop-and-go outperforms the rest in terms of convergence rate and MSE.

16-QAM 신호에 대한 CCA 적응 등화 알고리즘 성능 분석

Abstract This paper deals with the performance anlysis of CCA adaptive equalization algorithm, that is used for reduction of intersymbol interference at the receiving side which occurs in the time dispersive communication channel. Basically, this algorithm is borned for the solving phase unrecovery problem in the CMA equalizer, and the comines the concept of DDA (Decision Directed Algorithm) and RCA (Reduce Constellation Algorithm). The DDA has a stable convergence characteristics in unilevel signal, but not in the number of levels in multilevel signal such as QAM, so it has unstable problem. The RCA does not provide reliable initial convergence. And even after convergence, the equalization noise due to the steady state misadjustment exhibited by it is very high as compared to DDA. For the solving the abovemensioned point, the CCA adaptive eualization alogorithm has borned. In order to performance analysis of CCA algorithm, the recovered signal constellation that is the output of the equalizer, the convergence characteristic by the residual isi and MD (maximum distortion), the SER characteristic are used by computer simulation and it was compared with the DDA, RCA respectively. As a result of simulation, the DDA has superior performance than other algoithm, but it has a convergence unguarantee and unstability in the multilevel signal. In order to solving this problem, the CCA has more good performance than RCA in every performance index.

Signal-to-Noise Ratio Estimation Algorithm for Advanced DVB-RCS Systems

This paper presents a signal-to-noise ratio (SNR) estimation algorithm for advanced Digital Video Broadcasting-Return Channel via Satellite (DVB-RCS) systems using adaptive coding and modulation (ACM) in the reverse link of broadband satellite systems. Due to the absence of a repetitive pilot symbol structure, SNR estimation has to be performed using the fixed symbol preamble data. Moreover, sporadic nature of data traffic on the return link causes variation in interference level from slot to slot and, therefore, the estimation has to be done within one traffic slot duration. Hence, it becomes necessary to use a combination of data-aided (DA) and decision-directed (DD) algorithms so as to make use of traffic data. A non-data-aided (NDA) estimator that was previously proposed by the authors for binary phase shift keying (BPSK) and QPSK schemes is extended to 8-PSK in a decision directed manner. This estimator shows improved performance over existing estimators. The inherent bias of DD approach at low values of SNR is reduced by using a hybrid approach, i.e., using the proposed estimator at moderate/high values of SNR and the moments-based estimator ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> ) at low values of SNR. Overall improved performance of the proposed hybrid estimator, in terms of accuracy and complexity, makes it an attractive choice for implementing ACM in advanced DVB-RCS systems.

Blind, fast and SOP independent polarization recovery for square dual polarization–MQAM formats and optical coherent receivers

We present both theoretically and experimentally a novel blind and fast method for estimating the State of Polarization (SOP) of a single carrier channel modulated in square Dual Polarization (DP) MQAM format for optical coherent receivers. The method can be used on system startup, for quick channel reconfiguration, or for burst mode receivers. It consists of converting the received waveform from Jones to Stokes space and looping over an algorithm until a unitary polarization derotation matrix is estimated. The matrix is then used to initialize the center taps of the subsequent classical decision-directed stochastic gradient algorithm (DD-LMS). We present experimental comparisons of the initial Bit Error Rate (BER) and the speed of convergence of this blind Stokes space polarization recovery (PR) technique against the common Constant Modulus Algorithm (CMA). We demonstrate that this technique works on any square DP-MQAM format by presenting experimental results for DP-4QAM, -16QAM and -64QAM at varying distances and baud rates. We additionally numerically assess the technique for varying differential group delays (DGD) and sampling offsets on 28 Gbaud DP-4QAM format and show fast polarization recovery for instantaneous DGD as high as 90% of symbol duration. We show that the convergence time of this blind PR technique does not depend on the initial SOP as CMA does and allows switching to DD-LMS faster by more than an order of magnitude. For DP-4QAM, it shows a convergence time of 5.9 ns, which is much smaller than the convergence time of recent techniques using modified CMA algorithms for quicker convergence. BER of the first 20 × 10(3) symbols is always smaller by several factors for DP-16QAM and -64QAM but not always for DP-4QAM.

MIMO-OFDM Channel Tracking Using a Dynamic ANN Topology

All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation. Keywords—MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.

Iterative Decision-Directed Joint Frequency Offset and Channel Estimation for KSP-OFDM

We propose an iterative decision-directed joint frequency offset (FO) and channel estimation algorithm in a known symbol padding (KSP) orthogonal frequency division multiplexing (OFDM) system, where the guard interval is filled with pilot symbols. Besides those time domain pilot symbols, some additional pilot symbols are transmitted on the pilot carriers. The decision-directed algorithm is initialized by pilot-aided FO estimation without channel knowledge. We propose a possible initialization algorithm that operates in the frequency domain (FD). After the initialization phase, the iterative decision-directed estimation algorithm is applied. For the channel estimation step, an existing pilot-aided channel estimation algorithm is extended to a decision-directed algorithm which uses the Fast Fourier Transform outputs at both the pilot and data carrier positions. For the uncoded case, the proposed iterative decision-directed joint FO and channel estimation algorithm reaches the bit error rate performance of a receiver with perfect synchronization and perfect channel knowledge. For a coded system, there is small loss in performance of less than 1 dB when our proposed algorithm is applied compared to a receiver with perfect knowledge about the FO and the channel.

Chaotic convergence of the decision-directed blind equalization algorithm

Classically, adaptive equalization algorithms are analyzed in terms of two possible steady state behaviors: convergence to a fixed point and divergence to infinity. This twofold scenario suits well the modus operandi of linear supervised algorithms, but can be rather restrictive when unsupervised methods are considered, as their intrinsic use of higher-order statistics gives rise to nonlinear update expressions. In this work, we show, using different analytical tools belonging to dynamic system theory, that one of the most emblematic and studied unsupervised approaches – the decision-directed algorithm – is potentially capable of presenting behaviors, like convergence to limit-cycles and chaos, that transcend the aforementioned dichotomy. These results also indicate theoretical possibilities concerning step-size selection and initialization.

Channel Estimation Algorithms for OFDM-IDMA: Complexity and Performance

In this paper, a number of channel estimation algorithms for iterative receivers are compared for the case of an up-link orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) system. Both pilot based algorithms, used to obtain an initial estimate, as well as semi-blind decision-directed algorithms working as a component of the iterative receiver are considered. Algorithms performing either joint minimum mean square error (MMSE) channel estimation, or iterative estimation using space-alternating expectation maximization (SAGE), are evaluated. The considered algorithms differ in terms of complexity, as well as performance. The main contribution of this paper is to give an overview of different channel estimation approaches for OFDM-IDMA, where the complexity versus performance tradeoff is at the focal point. There is no single channel estimator providing the best tradeoff and our analysis shows how the system load (number of users) and the SNR influence the estimator choice.

Performance analysis of decision directed maximum likelihood MIMO channel tracking algorithm

SUMMARYIn this paper, the performance of decision directed (DD) maximum likelihood (ML) channel tracking algorithm is analyzed. The ML channel tracking algorithm presents efficient performance especially in the decision directed mode of the operation. In this paper, after introducing the method for analysis of DD algorithms, the performance of ML MIMO channel tracking algorithm in the DD mode of operation is analyzed. In this method channel tracking error is evaluated for a given decision error rate. Then, the decision error rate is approximated for a given channel tracking error. By solving these two derived equations jointly, both the decision error rate and the channel tracking error are computed. The presented analysis is compared with simulation results for different channel ranks, Doppler frequency shifts, and signal‐to‐noise ratios, and it is shown that the analysis is a good match for simulation results especially in high rank MIMO channels and high Doppler shifts. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Signal-to-noise ratio estimation algorithm for adaptive coding and modulation in advanced digital video broadcasting–radar cross section satellite systems

This paper presents a signal-to-noise ratio (SNR) estimation algorithm for advanced digital video broadcasting- return channel via satellite (DVB-RCS) systems using adaptive coding and modulation (ACM). Due to the absence of a repetitive pilot symbol structure, SNR estimation has to be performed using the fixed symbol preamble data. Moreover, sporadic nature of data traffic on the return link causes variation in interference level from slot to slot and, therefore, the estimation has to be done within one traffic slot duration. Hence, it becomes necessary to use a combination of data-aided and decision-directed (DD) algorithms so as to make use of traffic data. A non-data-aided estimator that was previously proposed by the authors for binary and quadrature phase shift keying schemes is extended to 8-PSK in a decision directed manner. The inherent bias of DD approach at low values of SNR is reduced by using a hybrid approach, that is, using the proposed estimator at moderate/high values of SNR and the moments-based estimator (M2M4) at low values of SNR. Overall improved performance of the proposed hybrid estimator, in terms of accuracy and complexity, makes it an attractive choice for implementing ACM in advanced DVB-RCS systems.

Decision-directed feedback equalisation for QAM signals

Proposed is a symbol-based decision-directed algorithm for blind equalisation of quadrature amplitude modulation (QAM) signals using a decision feedback scheme. Independently of QAM order, it presents: (i) an error equal to zero when the equaliser output coincides with the transmitted signal; (ii) simultaneous recovery of the modulus and phase of the signal; (iii) a misadjustment close to that of the normalised least-mean squares algorithm; (iv) fast convergence; and (v) the avoidance of degenerative solutions. Additionally, its stability is ensured when the step-size is properly chosen.

계산 복잡도가 줄어든 새로운 Bussgang 자력 등화 알고리듬

눈 모형이 열린 경우 간결하고 좋은 수렴 특성을 갖는 결정-지향 자력 등화 알고리듬이 자주 사용된다. 그러나 눈 모형이 닫힌 채널에서 결정-지향 알고리듬의 수렴은 보장되지 않는다. 이러한 문제를 해결하기 위하여 무기억 비선형 함수로 hyperbolic tangent 함수를 사용하는 수정된 Bussgang 알고리듬의 적용이 Filho 등에 의하여 제안되었다. 그러나 이 알고리듬의 적용은 hyperbolic tangent 함수 그리고 이의 미분에 대한 계산 및 채널의 변화에 따른 룩업 테이블을 위한 많은 메모리를 필요로 한다. 따라서 본 논문에서는 Filho 등이 제안한 알고리듬의 계산량 또는 하드웨어 복잡도를 줄이기 위하여 결정-지향 알고리듬을 위한 개선된 기법을 제안한다. 무기억 비선형 함수를 signum 함수로 설정하고, 이의 미분인 디락 델타 함수(Dirac delta function)를 협소한 사각 펄스로 근사화하여 결정-지향 알고리듬에 적용하면 Filho가 제안한 알고리듬의 수렴 및 정상 상태 성능은 유지하면서 계산 복잡도를 크게 줄일 수 있다. The decision-directed blind equalization algorithm is often used due to its simplicity and good convergence property when the eye pattern is open. However, in a channel where the eye pattern is closed, the decision-directed algorithm is not guaranteed to converge. Hence, a modified Bussgang-type algorithm using a hyperbolic tangent function for zero-memory nonlinear(ZNL) function has been proposed and applied to avoid this problem by Filho et al. But application of this algorithm includes the calculation of hyperbolic tangent function and its derivative or a look-up table which may need a large amount of memory due to channel variations. To reduce the computational and/or hardware complexity of Filho's algorithm, in this paper, an improved method for the decision-directed algorithm is proposed. In the proposed scheme, the ZNL function and its derivative are respectively set to be the original signum function and a narrow rectangular pulse which is an approximation of Dirac delta function. It is shown that the proposed scheme, when it is combined with decision-directed algorithm, reduces the computational complexity drastically while it retains the convergence and steady-state performance of the Filho's algorithm.

변형된 CMA의 수렴상수 갱신 방법의 성능 비교

변형된 CMA는 CMA에 비해 고차 신호점을 등화 시 보다 적은 수의, 균등한 간격을 갖는 모듈러스를 이용함으로써 정상상태 성능 개선과 고차 신호점으로의 확장이 용이하다. 본 논문에서는 변형된 CMA에 가변 수렴상수를 적용하여 정상상태 성능을 더욱 개선하여 다른 경판정 알고리즘으로의 전환 없이도 충분히 만족스러운 성능을 달성할 수 있음을 보인다. 새로운 두 가지 수렴상수 가변 방법을 제안하고, 이를 적용한 변형된 CMA의 성능 개선을 모의실험을 통해 CMA와 고정 수렴상수의 변형된 CMA에 대해 확인하였다. Compared to the constant modulus algorithm (CMA), the modified CMA (MCMA) is easy not only to improve the steady-state performance but also to be expanded to higher-order constellations by using fewer moduli with evenly spaced. In this paper, it is shown that the MCMA is sufficient to achieve satisfactory steady-state performance by applying a variable step-size to the MCMA without switching to an hard decision-directed algorithm. Two new methods varying the step-size are proposed, and the performance improvement of the MCMA with the new methods of variable step-size is presented as compared to the CMA and the fixed step-size MCMA through computer simulations.