Iterative soft-minimum mean-square error equalization for digital nonlinear page-oriented memories

Digital page-oriented volume holographic memory (POVHM) is a promising candidate for next-generation ultrahigh capacity optical data storage technology. As the capacity of the POVHMs increases, the bit error rate performance of the system is degraded due to increased interpixel interference (IPI) and noise. To improve the system performance under these adverse effects and to increase the capacity, joint iterative soft equalization-detection and error correction decoding might be attractive. To address that, by considering the nonlinearity inherent in the channel, an iterative soft equalization method that is optimized in the minimum mean-square error (MMSE) sense, called the iterative soft-MMSE (ISMMSE) equalization, is devised. The performance of the ISMMSE is evaluated by use of numerical experiments under different amounts of IPI and optical noise. Simulation results suggest that the ISMMSE is a good candidate for an ultrahigh capacity POVHM, which employs joint iterative equalization-detection and decoding.     

Discrete magnitude-squared channel modeling, equalization, and detection for volume holographic storage channels

As storage density increases, the performance of volume holographic storage channels is degraded, because intersymbol interference and noise also increase. Equalization and detection methods must be employed to mitigate the effects of intersignal interference and noise. However, the output detector array in a holographic storage system detects the intensity of the incident light's wave front, leading to loss of sign information. This sign loss precludes the applicability of conventional equalization and detection schemes. We first address channel modeling under quadratic nonlinearity and develop an efficient model named the discrete magnitude-squared channel model. We next introduce an advanced equalization method called the iterative magnitude-squared decision feedback equalization (IMSDFE), which takes the channel nonlinearity into account. The performance of IMSDFE is quantified for optical-noise-dominated channels as well as for electronic-noise-dominated channels. Results indicate that IMSDFE is a good candidate for a high-density, high-intersignal-interference volume holographic storage channel.     

Soft-decision array decoding for volume holographic memory systems

We study the use of soft-decision array decoding in a volume holographic memory (VHM) system that is corrupted by interpixel interference (IPI) and detector noise. Soft-decision methods can unify equalization and error decoding. A highly parallel array decoder is presented in the context of two-dimensional low-pass channel mitigation and error correction. The new decoding algorithm is motivated by iterative turbo-decoding methods and is capable of incorporating a priori knowledge of the corrupting IPI channel during decoding. The resulting joint detection decoding algorithm is shown to offer VHM capacity and density performance superior to that of hard-decision n = 255 Reed-Solomon codes in concatenation with a Wiener filter.     

Cancellation of Linear Intersymbol Interference for Two-Dimensional Storage Systems

This paper discusses the cancellation of linear intersymbol interference (ISI) in two-dimensional (2-D) systems. It develops a theory for the error rate of receivers that use tentative decisions to cancel ISI. It also formulates precise conditions under which such ISI cancellation can be applied effectively. For many 2-D systems, these conditions are easily met, and therefore the application of ISI cancellation is of significant interest. The theory and the conditions are validated by simulation results for a 2-D channel model. Furthermore, results for an experimental 2-D optical storage system show that, for a single-layer disk with a capacity of 50 GB, a substantial performance improvement may be obtained by applying ISI cancellation.     

Nonlinear equalization for holographic data storage systems

Despite the fact that the channel in a holographic data-storage system is nonlinear, most of the existing approaches use linear equalization for data recovery. We present a novel and simple to implement nonlinear equalization approach based on a minimum mean-square-error criterion. We use a quadratic equalizer whose complexity is comparable to that of a linear equalizer. We also explore the effectiveness of a nonlinear equalization target as compared with the conventional linear target. Bit-error-rate (BER) performance is studied for channels having electronics noise, optical noise, and a different span of intersymbol interference. With a linear target, whereas the linear equalizer exhibits an error floor in the BER performance, the quadratic equalizer significantly improves the performance with no sign of error floor even up to 10(-7). With a nonlinear target, whereas the quadratic equalizer provides an additional performance gain of 1-2 dB, the error-floor problem of the linear equalizer has been considerably alleviated, thereby significantly improving the latter's performance. A theoretical performance analysis of the nonlinear receiver with non-Gaussian noise is also presented. A simplified approach is developed to compute the underlying probability density functions, optimum detector threshold, and BER using the theoretical analysis. Numerical results show that the theoretical predictions agree well with simulations.     

Media limitations on achievement of maximum detection window

The recording performance of a digital recording system is primarily dependent upon the isolated half pulse width (T50), signal amplitude, intersymbol interference (ISI), signal to noise ratio (SNR) and the horizontal detection window margin (Tm). These characteristics are related to the thickness and magnetic properties of the media, as well as the head/media interface. This paper addresses the relationship of the media characteristics in longitudinal digital magnetic recording for both particulate and thin film media to the overall recording system performance. The results are shown to proceed from further development of the quasi-optimum time containment filter analysis for media noise dominant and electronic (white) noise dominant recording channels [1], [2].     

Communication theoretic image restoration for binary-valued imagery

We present a new image-restoration algorithm for binary-valued imagery. A trellis-based search method is described that exploits the finite alphabet of the target imagery. This algorithm seeks the maximum-likelihood solution to the image-restoration problem and is motivated by the Viterbi algorithm for traditional binary data detection in the presence of intersymbol interference and noise. We describe a blockwise method to restore two-dimensional imagery on a row-by-row basis and in which a priori knowledge of image pixel correlation structure can be included through a modification to the trellis transition probabilities. The performance of the new Viterbi-based algorithm is shown to be superior to Wiener filtering in terms of both bit error rate and visual quality. Algorithmic choices related to trellis state configuration, complexity reduction, and transition probability selection are investigated, and various trade-offs are discussed.     

Variable-length two-dimensional modulation coding for imaging page-oriented optical data storage systems

We present what is to our knowledge a new class of two-dimensional (2-D) modulation codes, called variable-length 2-D modulation codes, suitable for page-oriented optical data storage (PODS) systems that write and read data in a 2-D bit image format. These codes overcome the inherent spatial intersymbol interference in imaging PODS systems and improve the code rate performance of previous fixed-length 2-D modulation codes. The codes in this new class map one-dimensional input data blocks of variable lengths to 2-D output data blocks of variable lengths and are designed to limit error propagation. In this study we give several examples of fixed-length and variable-length 2-D modulation codes with various properties for imaging PODS systems. We also compare the bit-error-rate performance of these fixed-length and variable-length codes.     

Application of linear minimum mean-squared-error equalization for volume holographic data storage

When target densities of volume holographic data storage systems are increased, the systems experience increased interference from adjacent pixels and noise. Here we present a method for designing and applying linear minimum mean-squared-error (LMMSE) equalization to improve the bit error rates (BER's) and hence the storage densities achievable. Numerical results with five defocused data pages indicate that a significant improvement in the BER is possible with LMMSE equalization.     

Characterization and spectral equalization for hight-density disk recording

For a 3350 type head/disk interface, the amplitude spectrum of an experimental characteristic pulse deviates slightly from the idealized Lorentzian distribution in the signal bandwidth; but the phase spectrum of the experimental pulse is quite distorted from the desired linear phase, causing the widely observed asymmetrical time-domain waveform. A quantitative characterization and comparison are presented and individual transfer functions for ideal linear equalization are proposed. To remove the intersymbol interference, i.e., the linear portion of the distortion, from the playback signal of a high-density system, several cosine-power-law spectral candidates, with minimized noise enhancement and the capability of restoring amplitude loss and timing error, are explored. A unified relationship for the entire family of cosine-power-law spectral shapes and their bandwidth tradeoffs are identified, allowing for optimum read equalization at a tolerable signal-to-noise penalty. This is a useful tool for exploring practical density limitations of any given head/disk interface.     

Transmitter pre-filtering for the downlink of a time-division-duplex/direct sequencecode division multiple access system over time-varying multipath fading channels

In this paper, we investigate an optimised transmitter pre-filtering technique for downlink time-division-duplex (TDD) code division multiple access (CDMA) communications, which employs the conventional matched filter (MF) detector at the mobile receivers. The proposed pre-filtering technique eliminates the multiple-access interference and intersymbol interference (MAI/ISI) effects by applying a very simple transmission scheme that combines a signal transformation with a cyclic prefix strategy under a power constraint condition. Two constrained pre-filtering transformations are suggested depending on the information required at the mobile unit. An open-loop transmitter pre-filtering is first formulated; however, this solution does not consider the properties of the noise at the mobile receiver. A second solution is then presented via a closed-loop transmitter pre-filtering that includes an optimum gain for a given transmit and noise power. Some associated issues such as system efficiency, computational complexity and channel estimation errors are also addressed. Simulation results show that the proposed transmitter pre-filtering scheme can be used to increase the system performance and capacity. In addition, its performance is compared with another similar transmit pre-processing scheme in order to evaluate the performance improvement by the proposed algorithm.     

Amorphous Sn modified nitrogen-doped porous carbon nanosheets with rapid capacitive mechanism for high-capacity and fast-charging lithium-ion batteries

Sn-based materials are considered as a kind of potential anode materials for lithium-ion batteries (LIBs) owing to their high theoretical capacity. However, their use is limited by large volume expansion deriving from the lithiation/delithiation process. In this work, amorphous Sn modified nitrogen-doped porous carbon nanosheets (ASn-NPCNs) are obtained. The synergistic effect of amorphous Sn and high edge-nitrogen-doped level porous carbon nanosheets provides ASn-NPCNs with multiple advantages containing abundant defect sites, high specific surface area (214.9 m²·g⁻¹), and rich hierarchical pores, which can promote the lithium-ion storage. Serving as the LIB anode, the as-prepared ASn-NPCNs-750 electrode exhibits an ultrahigh capacity of 1643 mAh·g⁻¹ at 0.1 A·g⁻¹, ultrafast rate performance of 490 mAh·g⁻¹ at 10 A·g⁻¹, and superior long-term cycling performance of 988 mAh·g⁻¹ at 1 A·g⁻¹ after 2000 cycles with a capacity retention of 98.9%. Furthermore, the in-depth electrochemical kinetic test confirms that the ultrahigh-capacity and fast-charging performance of the ASn-NPCNs-750 electrode is ascribed to the rapid capacitive mechanism. These impressive results indicate that ASn-NPCNs-750 can be a potential anode material for high-capacity and fast-charging LIBs.     

水声通信中变步长神经网络盲均衡算法研究

在水声通信领域多途引起的码间干拢可以用均衡消减。盲均衡不需要训练序列,这将有效的节省通信带宽,提高通信效率及通信性能。实际中的通信信道不可能是完全线性的,神经网络作为一种非线性动态系统,具有大规模并行处理及高度的鲁棒性特征,将其应用于水声信道盲均衡切实可行。文中对变步长BP算法的前馈神经网络进行了理论和算法分析,并通过计算机对其实现水声信道盲均衡进行了仿真。仿真结果表明采用变步长BP算法比采用传统BP算法的神经网络盲均衡器收敛速度快,均衡性能明显提高。     

Improving adaptive receivers performance in molecular communication via diffusion

Forthcoming applications for molecular communications (MC) such as drug‐delivery and health monitoring will require robust receiver capabilities to mitigate channel memory and inter symbol interference caused by previous transmitted symbols. Here, the authors introduce an adaptive weighted algorithm to reduce the influence of these factors. This novel signal detection is deployed on to a concentration‐based MC system with absorbing receiver which is based on the so‐called first passage time concept. The proposed detector has low complexity and does not require explicit channel knowledge. To evaluate authors’ proposed algorithm, a theoretical approach is developed to derive the bit error rate (BER). Numerical results also carried out to verify the accuracy of these formulations and establish that the new detector will achieve better performance in comparison with other common low‐complex detectors under certain scenarios. Additionally, the authors propose a simple pre‐coding technique to combat the sequence of consecutive ones in low ISI scenarios. Also a comparison between detectors is given, which is based on the variation of distance, symbol period, signal‐to‐noise ratio (SNR), and number of molecules.Inspec keywords: radio receivers, error statistics, signal detection, intersymbol interferenceOther keywords: low‐complex detectors, low ISI scenarios, symbol period, signal‐to‐noise ratio, adaptive receivers performance, molecular communication, drug‐delivery, health monitoring, robust receiver capabilities, channel memory, inter symbol interference, previous transmitted symbols, adaptive weighted algorithm, novel signal detection, concentration‐based MC system, absorbing receiver, passage time concept, low complexity, explicit channel knowledge, authors, theoretical approach, bit error rate, numerical results     

Fixed-length two-dimensional modulation coding for imaging page-oriented optical data storage systems

We present a comprehensive discussion of modulation coding for page-oriented optical data storage (PODS) systems that write and read data in a two-dimensional (2-D) bit image format. We give several 2-D mathematical models for these systems, including two-photon optical data storage systems. Using these models, we describe the nature of intersymbol interference (ISI) in imaging PODS systems and find that its characteristics are different from ISI in conventional serial magnetic and optical data storage systems. To overcome the ISI in these imaging PODS systems, we present what is, to our knowledge, a novel 2-D modulation coding scheme. We also present many examples of fixed-length 2-D modulation codes with diverse properties. Finally, we analyze and compare the bit-error rate performance of these codes.     

Blockwise data detection for spectral hole-burning memories

We consider the retrieval of data from a time-domain spectral hole-burning (SHB) memory system. A new iterative log-likelihood (ILL) algorithm is used to reliably detect corrupted retrieved data signals. It is a blockwise technique that takes advantage of the known SHB system characteristics to mitigate time-varying intersymbol interference and detector shot noise. We present bit-error-rate results obtained with the ILL algorithm and five other typical methods (i.e., precompensator, simple threshold, adaptive threshold, a simple Wiener filter, and an adaptive Wiener filter). Results show that the ILL algorithm outperforms all five techniques and hence offers improved SHB storage capacity. In a SHB system with typical material parameters, we find that ILL offers a storage capacity gain of 197% as compared with simple thresholding.     

Signal detection for page-accessoptical memories with intersymbol interference

We propose a technique for data detection in a two-dimensional page-access optical memory. The technique combines sequence detection by the use of the Viterbi algorithm with decision feedback to improve the bit-error-rate performance in a system corrupted by intersymbol interference. It has an advantage in that it can be operated on a row-by-row basis as data are output from the optical detector. Use of the proposed scheme might ease the design tolerances of the optical components or permit the use of large data pages.     

Investigation of multilevel amplitude modulation for a dual-wavelength free-space optical communications system using realistic channel estimation and minimum mean-squared-error linear equalization

Fog is a highly dispersive medium at optical wavelengths, and the received pulse waveform may suffer significant distortion. Thus it is desirable to have the impulse response of the propagation channel to recover data transmitted through fog. The fog particle density and the particle size distribution both strongly influence the channel impulse response, yet it is difficult to estimate these parameters. We present a method using a dual-wavelength free-space optical system for estimating the average particle diameter and the particle number density and for approximating the particle distribution function. These parameters serve as inputs to estimate the atmospheric channel impulse response using simulation based on the modified vector radiative transfer theory. The estimated channel response is used to design a minimum mean-square-error equalization filter to improve the bit error rate by correcting distortion in the received signal waveform due to intersymbol interference and additive white Gaussian noise.     

钻柱声传输信号多载波调制激励分析

在随钻声遥测技术中,周期性钻柱结构产生的多重回波极易造成严重的码间干扰和较高误码率,为此,根据钻柱信道的多径传输特性,基于短钻杆条件下多载波传输的实验分析,建立了多节钻杆与管箍的周期性信道有限差分模型。考虑地面噪声和信道内多径回波干扰,利用最小均方自适应均衡,基于“4钻杆—3管箍”信道结构进行了多载波调制性能仿真分析。仿真结果表明,与单载波PSK（Phase-Shift-Keying）调制相比,OFDM（Orthogonal Frequency Division Multiplexing）多载波调制可使误码率平均降低约50%;在非周期性结构下其传输性能受信道变化敏感,但相同条件下仍优于PSK调制,且通过子载波相位补偿可有效改善误码率、提高传输性能。     

Design of multilevel decision feedback equalizers

Multilevel decision feedback equalization scheme (MDFE) is an efficient and simple realization of the fixed-delay tree search with decision feedback (FDTS/DF) for channels using RLL(1,k) codes. In MDFE, the entire tree-search is replaced with a 2-tap transversal filter and a binary comparator with negligible loss in performance. This 2-tap filter can be combined with the forward and feedback equalizers resulting in a structure that is physically identical to DFE but requires very different equalizer settings. This paper focuses on equalizer design for MDFE. It is first shown that the MDFE scheme can also be derived without using the principle of tree-search by exploiting the run-length constraints imposed by the RLL(1,k) code in conjunction with the maximization of an appropriately defined signal-to-noise ratio (SNR). Recognizing that a multilevel eye Is formed at the comparator, we define this SNR as the eye-opening divided by noise plus intersymbol interference. This formulation directly leads to a novel adaptive scheme based on the well known LMS algorithm. The relationship between this work and the earlier derivation of MDFE is then clarified. We also develop a noniterative analytical approach for the optimum equalizer design. Because of the economy of implementation, there is particular interest in the design of continuous-time forward equalizers. A noniterative analytic design approach, which does not suffer from local minima problems, is developed for such equalizers. Computer simulation results are presented for comparing the different design approaches