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Today, we are evident to the revolution of the automotive industry and its demand for high bandwidth sensor fusion. Multiple high bandwidth sensors are connected, generating tremendous amount of data to be transferred in real-time in harsh environment, i.e., multi-gigabit intra-vehicle networks. Plastic optical fiber (POF) is an attractive medium for these multi-gigabit intra-vehicle networks due to its inherent EM compatibility, galvanic isolation, low weight, high tolerance to mechanical vibrations, low bending loss, and easy handling. However, commercial off-the-shelf PMMA based POFs are bandwidth-length product limited. Here, we suggest increasing the spectral efficiency using spatial-division multiplexing (SDM). In this article, we have experimentally demonstrated a low cost and eye-safe 3 × 3 multiple-input multiple-output (MIMO) SDM system over a 15 meters multicore (MC) POF using commercial optical components, e.g., RC-LEDs and Si-PIN photodiodes. A 3 × 1 spot-based cores coupler spatial multiplexer was developed to couple the optical components with the MC-POF. This system achieved raw data rates of 1.5 Gb/s and 2.4 Gb/s using offline-processed MIMO equalization. The proposed system enables a flexible and scalable optical MIMO system that can meet the requirements of the automotive industry.

Analog distortion compensation based on digital signal processing methods are widely applied for transmitter or receiver impairments in various digital communication systems. Recently, several neural network methods were developed for distortion compensation. However, while digital communication systems are typically complex-valued, neural networks are mostly designed to work with real-valued inputs. Thus, adaptations of the network architecture or input data should be applied. In this article a method for using a single-input real-valued neural network for digital communication-based complex-valued signals without any modifications to the neural network is proposed. The method transforms the complex-valued signal to a real-valued one by taking the real component of a complex frequency offset applied through digital up-conversion, without affecting the distortion, therefore allowing standard neural network-based functionality with significant reduction in size. The method is tested with a multi-layer perceptron and gated recurrent unit architectures applied over a generic Wiener-Hammerstein model for the case of equalization of a coherent optical system. A reduction of about 7% and 26% in network size is shown for the gated recurrent unit-based and multi-layer perceptron-based architectures respectively, without any significant change in performance. This size reduction capability shows the high potential in applying the proposed method in neural network-based equalization and pre-distortion operations.

High throughput coherent optical transmitters are key components in future optical communication infrastructure. However, these transmitters are often distorted with the nonlinearity of their components. A potential approach for compensating nonlinearity is by applying digital pre-distortion methods based on the Volterra series or one of its derivatives. However, the Volterra series-based solution is complex to implement, difficult to scale, and its simplified versions may not yield the desired performance. Recently digital pre distortion solutions based on neural networks were proposed, which may benefit from the generality of neural networks and can be more easily scaled. These solutions are often based on non-standard neural network architectures which require complex neurons-based architectures or being based on indirect training approach which suffer from noise enhancement. In this article, a novel method for neural network-based pre-distortion with direct learning is proposed. The direct learning with neural network does not assume a specific transmitter model and does not suffer from noise enhancement. The method assumes standard neural network inference architecture and is applied to a coherent nonlinear optical transmitted with long-short-term memory neural network. The overall performance and complexity of the direct learning method is compared with the indirect approach and with the Volterra series-based solution, showing significant advantage in performance, especially in cases of severe nonlinearity and noise conditions.

DSP techniques that enhance the effective resolution of digital-to-analog converters (DACs) are presented. First, DACs that are limited by physical number of bits (PNOB) are addressed. An improved digital-resolution-enhancer (DRE) algorithm, which incorporates an optimized non-uniform quantization scheme is analytically analyzed and experimentally demonstrated. Improvement of up to 8 dB is shown, that enables 16QAM and 64QAM transmission using only 2 and 3 bits DACs, respectively. Furthermore, the DRE concept is elaborated to include additional practical DAC impairments such as timing jitter. Based on a generalized DAC model, we suggest an improved algorithm that increases the tolerance to jitter noise, termed as jitter-aware DRE (JA-DRE). The method is validated in numerical simulations, indicating substantial OSNR gain of $\sim \!5$ dB over non DSP enhanced DACs, and up to 2 dB over the previously proposed DRE algorithm.

A stealthy and encrypted transmission is demonstrated in a dense-WDM network. The residual gap between two neighboring commercial channels is utilized for the transmission of the secured channel, hidden below the amplifier noise at negative −10 dB/0.1nm OSNR. The stealthy and encrypted channel is generated by a digital replication of the baseband signal together with a digital spectral phase mask. This technique provides encryption and steganography as it exclusively allows the eligible user to obtain a considerable processing-gain, and to recover extremely low OSNR signals. In this work the secured channel is explored under stringent network conditions. A stealth transmission was tested between two high OSNR public channels, separated 50 GHz apart: Unshaped 25 Gbps NRZ channel and digitally shaped coherent PM-QPSK 112 Gbps channel. Although it is significantly overlapped by adjacent channels and covered by the ASE noise, we demonstrate error-free detection of the secured channel, without significant effect on the commercial channels.

Digital signal processing (DSP)-based system is a common architecture for high-speed communication links. One of the most important components for DSP-based architectures is the analog-to-digital convertor (ADC). Most of the high-speed ADCs are implemented as time interleaved ADC (TI-ADC). One of the major challenges in TI-ADC is the timing mismatch between the parallel sub-ADCs. The calibration of this mismatch increases system cost and complexity. In this article we propose a new background calibration method based on existing clock and data recovery (CDR) circuits. The timing mismatch can be calibrated using a simple and unique CDR per sub-ADC. Using the existing phase error detector and pulse gain estimator of the regular CDR, the calibration circuit becomes very low-cost, requiring only a first order loop, and a slow numerically controlled oscillator (NCO). VCSEL-based lab experiments are performed, which demonstrate the proposed method efficiency, performance and robustness.

High-speed optical communication systems may suffer from a combination of impairments such as memory effect and nonlinear behavior of the optoelectronic components. Nonlinear digital pre-distortion (DPD) is one of the well-known technique to alleviate these effects. As typical implementation of Volterra-based DPD is considered complex and consumes high power, more efficient orthogonal-based Volterra series representation has been proposed. Previous works offered ways to perform efficient grading of the most dominant dimensions based on the combination of the dimensions variances and the signal projection. Here, it is shown that normalization of the data dynamic range further improves this method and decreases significantly the number of required dimensions. Using normalization combined with the previous methods, maximizes the DPD performance by means of error vector magnitude (EVM) and bit error rate (BER), while minimizing the DPD complexity in the terms of required series dimensions. Extensive simulation and lab measurements indicate a potential saving of up to 87% in the number of dimensions with a negligible performance penalty.

An analog fractionally spaced equalizer (FSE) is an efficient solution for high-speed communication system without a clock and data recovery circuit. However, the FSE might become unstable when a sign–sign least mean square tuning algorithm is used, especially when the transmitter pre-distortion is used. Here, an analytical model of the instability is derived, and a low-cost and efficient stabilization process based on dithering is proposed. The analytical instability model is verified in an experimental setup based on a vertical cavity surface emitting laser. Furthermore, it is experimentally demonstrated that in the case of the instability of the FSE, a clear convergence is achieved when applying the proposed stabilization scheme.

Digital pre-compensation (DPC) is an indispensable block of state-of-the-art optical transceivers, and a key enabler for high-order modulation formats (HOMFs) transmission. A crucial component, which enables the transmission of the precompensated HOMFs, is the digital-to-analog-converter (DAC). However, as data and symbol rates grow, the implementation of such devices becomes highly challenging in terms of performance, power consumption, and costs. In this paper, a digital-resolution-enhancer (DRE) algorithm is discussed, conjoined with high-end DPC methods. Simulation results demonstrate that the DRE reduces the effect of DAC quantization noise power by more than 8 dB for the considered cases of 400G with 64QAM. The proposed scheme is experimentally verified by transmitting a 4-bit DP-64QAM 400 Gbit/s signal in a WDM scenario over 95 km of single mode fiber.

A novel all-optical stealth and secured transmission is proposed and demonstrated. Spectral replicas of the covert signal are carried by multiple tones of a gain switched optical frequency comb, optically coded with spectral phase mask, and concealed below EDFA’s noise. The secured signal’s spectrum is spread far beyond the bandwidth of a coherent receiver, thus forcing real time all-optical processing. An unauthorized user, who does not possess knowledge on the phase mask, can only obtain a noisy and distorted signal, that cannot be improved by post-processing. On the other hand, the authorized user decodes the signal using an inverse spectral phase mask and achieves a substantial optical processing gain via multi-homodyne coherent detection. A transmission of 20 Gbps under negative −7.5 dB OSNR is demonstrated here, yielding error-free detection by the eligible user.

Digital precompensation (DPC) is considered a promising technique for high-throughput optical communication systems. The digital signal processing (DSP) at the transmitter relies on the availability of high-speed and high-resolution digital-to-analog devices to generate complex analog waveforms. However, one major challenge in current digital-to-analog converters (DACs) technology is the limited resolution, which introduces dominant quantization distortions when extensive DSP is implemented. In this paper, a dynamic quantization approach is suggested, termed as digital-resolution-enhancer (DRE), which mitigates the quantization distortion effects. This approach is based on the underlying assumption that quantization is a non-linear deterministic operation, implying that its impact on transmission can be anticipated and minimized. The proposed method is theoretically and experimentally investigated with special focus on linear precompensation for bandwidth limited systems. Simulation results demonstrate that the DRE improves the signal-to-quantization noise-ratio by up to 8 dB. Thus, the DPC can be applied with the reduced number of DAC's bits. Conversely, the DRE can enable the use of more complex DPC schemes using the same DACs hardware, and consequently, achieve extended reaches and higher transmission rates. Numerical simulations are verified by a set of extensive lab experiments. For electrical back-to-back (BTB) transmission, with an analog bandwidth of 13 GHz, 45 Gbaud QAM-64 is demonstrated using only 4 bits DACs. For optical BTB setup with an overall optoelectronic bandwidth of less than 5 GHz, 32 Gbaud QAM-4 is demonstrated using only 2.6 bits DACs.

Digital pre-compensation complementary to post equalization increases the digital signal processing (DSP) compensation envelope, especially in non-linear band-limited channels. The DSP at the transmitter relies on the availability of high-speed and high-resolution digital-to-analog devices to generate complex analog waveforms. However, one major challenge in high-speed digital-to-analog converter (DACs) technology is the limited resolution, which introduces dominant quantization distortions. Here, a new dynamic quantization technique is proposed, based on the fact that the quantization is a non-linear deterministic operation. Extensive lab experiments and numerical simulations demonstrate signal to quantization noise ratio improvement of up to 8 dB. In addition, an extremely low complexity modified Volterra digital pre-distortion (DPD) is developed, using orthogonal polynomial basis functions. Efficient grading method of the most dominant orthogonal dimensions is developed. The method combines both the dimensions variances and the impact of the information projection on each of the dimensions. The newly proposed modified Volterra DPD is shown to maximize the DPD performance while minimizing the number of required series dimensions. Extensive sets of lab experiments and simulations are performed, indicating potential saving of up to 89% in the amount of useful dimensions with a negligible error vector magnitude (EVM) penalty.

Optical communication systems often include nonlinear components, such as Mach-Zehnder modulators (MZMs). The components' nonlinearity may have a deleterious effect on the system performance, especially when the memory effect is included. One of the most common methods to mitigate the resultant distortion effects is digital predistortion (DPD) based on the Volterra polynomial model. Typically, the DPD coefficients are extracted using the least squares approach. However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. The orthogonal basis enables the estimation of each coefficient separately, which provides a significant computational gain. Furthermore, the amount of dominant terms in the orthogonal basis representation is significantly lower, which leads to dramatic relaxation in the DPD implementation. In addition to the analytical modeling approach, a nonparametric method is developed by applying eigenvalue decomposition on the correlation matrix, which is required for the case of dependent random variables, or for the case of unknown probability distribution functions. MZM-based lab experiments and simulations were performed, which indicated a potential saving of 50%-80% in the amount of useful dimensions.

The exponential growth of network traffic within data centers and high-performance computing generates a growing volume of fiber cabling. This raises the need for spectrally efficient communication scheme, which allows easy integration of optics and electronics. In this paper, we suggest a mode group division multiplexing scheme based upon intensity-modulated silicon photonics (SiP) Mach-Zehnder modulators (MZMs) coupled to standard graded-index multi-mode fiber directly detected using multi-segment concentric photo-detector. In addition, we have theoretically derived the bit and power loading of such a system in a closed-loop multiple-input multiple-output (MIMO) formation using convex optimization with two possible types of architectures: the vertical Bell Labs layered space-time architecture (V-BLAST) with minimum mean square error and successive interference cancellation (MMSE-SIC); and singular value decomposition (SVD). Our optimization problem maximizes the system's capacity under peak amplitude, power consumption, and BER constraints. Simulation results have shown the superiority of a V-BLAST MMSE-SIC over the SVD architecture in terms of total spectral efficiency for a 4 × 4 MIMO short reach low driving voltage conventional SiP-based MZM system.

A method for optical fiber equalization using neural network is proposed. The method uses digital up-conversion for processing the complex valued signal with significant reduction in network size without impact on equalization performance.

A gradual training paradigm for Recurrent Neural Network-based pre-distorter is proposed. Stochastic decomposition is used to separate nonlinearity and quantization noise features. Performance improvement of more than 6dB is presented.

An efficient timing skew calibration of time-interleaved ADC (TI-ADC) for high-speed link is proposed and experimentally validated. The method is based on the CDR’s existing sub-blocks and enables flexible tradeoff of complexity versus performance.

The optical transmitter components may cause nonlinear distortions mixed with memory effect. Using a system model identification scheme based on Volterra series, enable distortion root cause identification and design of efficient compensators to mitigate these effects.

The frequency-dependent dispersion impairment of high-speed printed analog traces in next-generation pluggable modules is studied. This frequency dependence is considered for the first time in optical fiber communication systems. Transmission of ultra-broadband electrical signals over such traces dramatically enhances the frequency-dependent dispersion effect. Here, for the first time, an extended model of the ultrabroadband signal transmission that includes this frequency-dependent dispersion effect of the printed analog traces is proposed. Additionally, a novel approach to compensate for this frequency-dependent dispersion impairment is introduced. Inclusive analysis reveals that a significant performance improvement of up to 4 dB is achieved by using the proposed symbol-spaced sampling and reduced-complexity digital signal processing technique.

We demonstrate a novel low-cost photonic-layer secured communication system that incorporates intensity modulation direct detection (IM/DD) scheme with a 4-level pulse amplitude modulation (PAM-4). In the proposed system, the signal is buried under an amplifier’s spontaneous emission (ASE) noise and coded with a spectral phase mask. As a result, the signal is stealthy and encrypted in both frequency and time domains. We analyze the reception performance of the secured signal under direct detection, and analytically compare its SNR with a conventional PAM-4 system, demonstrating that only an eligible receiver achieves a decryption of the stealthy and encrypted signal. Furthermore, we experimentally validate these findings showing a significant processing gain, which allows an error-free reception, despite a negative optical-SNR.

An efficient grading method for dimensions-reduced digital pre-distorter based on orthogonal Volterra series for band-limited nonlinear components is proposed. The method is based on a combination of dimension variance and signal-projection.

Employing DACs with low resolution plays a significant role in reducing the transponder power consumption. We experimentally verified the benefit of a digital resolution enhancer by transmitting WDM 400G-64QAM using a 4 physical bits DAC over DCI distances.

We show in an experiment a covert transmission of QPSK and 64-QAM over up to 100km of SSMF, digitally encrypted with spectral phase mask, buried under ASE noise with negative -15 dB/0.1nm OSNR. We record a post-FEC error free BER for a stealthy channel, at 16 Gbps on a single polarization.

As data centers evolve to sustain the economic scale in network traffic, optical interconnections are adapted to support the vast amount of capacity requirements. Among emerging solutions is the incorporation of digital-signal-processing (DSP) functionalities at the receiver to compensate for the optical fiber and optoelectronic components impairments. The bottleneck in such architecture is often implementing a high-resolution and high-speed analog-to-digital-converter (ADC) device, which usually leads to massive power consumption and high costs. In this paper, we propose novel transmission schemes based on low-resolution ADCs, termed DSP-enhanced analog-to-digital conversion. The proposed methods are based on the mathematical principle of predictive quantization, combined with linear equalization theory. Mathematical analysis and performance bounds associated with common channel impairments are derived. Simulation results demonstrate that the DSP-enhanced ADC provides a significant signal-to-noise-ratio (SNR) gain and, subsequently, may enable heavy digital compensation with reduced-resolution ADCs.

Optical communication networks use electrical constellation converters requiring optical–electrical–optical conversions and expensive symbol-rate limiting electronics. In this paper, a generic method for all-optical silicon-photonic conversion of amplitude–phase modulation formats is proposed. The method is based on the implementation of single-layer radial basis function neural networks. A mathematical model is developed, and the parameters influencing the performance of the method are analyzed. Full optical simulation of a four-symbol constellation conversion was performed, resulting in error-free converted constellation that has an error vector magnitude lower than 2.5%.

We experimentally demonstrate a 100 G ADC-MLSE-based 4-lanes NRZ direct detection transceiver. The DSP engine enables the use of low cost 10 G optoelectronics and supports 40 km metro transmission suitable for both ASE limited and point-to-point applications. The fully implemented mixed signal ASIC is based on standard 65 nm CMOS process.

A novel MIMO equalization architecture optimized for baud rate clock recovery (BCR-MIMO) in coherent 112 Gbit/sec dual polarization quadrature phase shift keying (DP-QPSK) metro systems is proposed. This architecture is designed to decouple between multiple-input-multiple-output (MIMO) equalization and clock recovery (CR) loops, avoiding the interaction between them. The decoupling between the two loops is achieved, while maintaining similar MIMO equalizer performance, as compared to the butterfly-structured equalizer.

A novel dynamic quantization algorithm is proposed to support pre-compensation using low resolution DACs. Electrical back-to-back 50Gbaud PAM-4 transmission over 11Ghz bandlimited infrastructure is demonstrated using 3 bits DAC.

A novel algorithm is proposed to overcome bandwidth limitation using low-resolution DACs. We demonstrate electrical back-to-back 32Gbaud QAM-64 over 11GHz and optical 32Gbaud QAM-4 over 5GHz using 4 bits and 2.6 bits DACs respectively.

Digital precompensation complementary to post equalization increases the DSP compensation envelope. Implementable parallel least square of nonlinear bandlimited channel, asymmetric imbalance predistortion of MZM impairments, and quantization noise preshaping minimizing DAC resolution requirement are presented.

Pre-distortion for an optical transmitter modeled with complex frequency selective nonlinearity applicable to different system architecture, based on recurrent neural network is proposed. Several architectures are compared and above 20dB performance gain is presented.

We propose a method for stealthy, covert, fiber-optic communication. In this method, the power of the transmitted signal is spread and lowered below the noise level both in time as well as in frequency domains which makes the signal “invisible”. The method is also efficient in jamming avoidance.

Encryption and steganography of the physical layer are experimentally demonstrated. We show a coherent stealthy transmission of 16 Gbps under negative −15 dB OSNR with pre-FEC BER of 1e-3, co-transmitted with public channel.

Recently we have proposed a method for temporal and spectral stealthy fiber-optic communications. In this technique the signal is spread in the time domain below the noise level and the power spectral density of the signal is spread beneath the noise level in the frequency domain. The power spectral density of the signal is reconstructed by means of sampling which results in coherent addition of the encrypted signal spectral replicas. Hence, the sampling quality plays a major role in the ability to successfully decrypt the received covert signal. In this paper, we mathematically and numerically analyze the effect of sampling impairments over the decryption performance.

Large-scale data centers store a huge amount of the world's data in their cloud servers. To ensure fast, reliable, low power, and low cost transmission, the communication channel between the server units is optical, at the highest available data rates of 100 – 400 Gbps. Consequently, all future solutions should rely on advanced communication techniques combined with high order modulation and digital signal processing (DSP).

An analog optimization of 4-level pulse amplitude modulation (PAM-4) signal is proposed, together with maximum likelihood sequence estimation digital signal processing. The proposed optimizations are verified by experimental demonstration at 53 Gbaud, indicating an improvement of 4&ndash, 5 dB in the optical signal to noise sensitivity.

Decision feedback equaliser (DFE) for dispersion compensation is a cost-effective element in optical communication OOK systems. The most common but sub-optimal optimisation criterion for the DFE weights is based on minimising the mean square error (MSE). Here, we derive an analytical expression for the probability of error with DFE and examine the optimal optimisation criterion, minimum bit-error rate (MBER) for DFE in optical communication system. A BER performance comparison analysis shows that the MBER optimisation criterion introduces improvements over the conventional minimum MSE optimisation criterion.

We propose a new compensation technique for coupling impairments of high-speed analog traces in chip-to-chip and chip-to-module connectivity in data centers. This technique significantly improves the performance and enables 100G PAM4 transmission.

This paper presents and analyzes a high-performance, robust, and scalable scheduling algorithm for input-queued switches called distributed sequential allocation (DISA). In contrast to pointer-based arbitration schemes, the proposed algorithm is based on a synchronized output reservation process, whereby each input selects a designated output while taking into consideration both local transmission requests and the availability of global resources. The distinctiveness of the algorithm lies in its ability to offer high performance when multiple cells are transmitted within each switching interval. Relaxed switching-time requirements allow for the incorporation of commercially available crosspoint switches. The result is a pragmatic and scalable solution for high port-density switching platforms. The efficiency of the scheme and its robustness in the presence of admissible traffic, without the need for speedup, is established through analysis and computer simulations. Performance results are shown for various traffic scenarios including nonuniform destination distribution, correlated arrivals and multiple classes of service.

Advances in digital hardware had enabled a new generation of fiber optics communication receivers. Extensive digital-signal-processing (DSP) allows compensating for channel impairments and, in turn, scaling up in data rate. One of the main challenges in modern receivers is implementing a high-rate, high-precision analog-to-digital-converter (ADC) that could meet the system requirements. Since ADCs technology is usually far from the highest rates available, reducing required resolution is imperative for present and future receivers. In this paper a predictive quantization approach is investigated. We show that common optical channel and components impairments introduce sufficient waveform correlation, which may be leveraged to significantly improve the Analog-to-digital-conversion process. Simulation results had shown that implementing low-complexity predictive quantization systems improves SNR performance, and may be used to reduce required resolution.

We propose coherent detection with one sample/symbol. Maximum-likelihood sequence estimation (MLSE) is used to compensate for intersymbol interference introduced by antialiasing filtering. The 100 000-ps/nm chromatic dispersion and 100-ps differential group delay are compensated with 1.5-dB penalty. Blind MLSE equalization is proposed.

A new optical communication system exhibiting a double security level is presented. Information coding is based on combined modulation formats of two data streams over the same optical carrier. Incoherent and coherent optical encryption algorithms are presented and are theoretically analyzed. The optical encryption method is transparent to data bit rates. Furthermore, it requires "on-line" data decoding with no possibility of recording and further processing. The incoherent scheme is very practical and can be implemented in existing optical communications systems, using currently available technology. Computer experiments of the incoherent method indicate less than 25 dB of signal to noise ratio required for 10-9 bit error rate and ineligible information decoding time of more than 10 8 years.

We propose a method that combines time division with multilevel signals in order to increase the channel capacity efficiently. This combined method enables increasing the bandwidth by a factor of , being the number of levels of the multilevel signal or alternatively enabling the transmission of independent channels, or any combination between both. This method increases bandwidth cost effectiveness and reduces the impact of fiber chromatic dispersion.

WDM is currently taking over as the leading technology in point-to-point transmission links. For optical implementation of WDM networks, logical functionalities such as wavelength (channel) selection should be carried out in the wavelength domain; thus, the development of dynamic optical devices is required. One key device is a tunable optical filter. Important features of such a filter include low insertion loss, narrow bandwidth, high sidelobe suppression, large dynamic range, fast tuning speed, a simple control mechanism, small size, and cost effectiveness. Here, an extensive overview of the different technologies used to produce tunable optical filters is presented. Among them, fiber filters such as fiber Bragg gratings and fiber Fabry Perot are the most commercialized, yet inherently limited in their dynamic speeds. For high demanding dynamics, micro-machined and acousto-optic filters can offer a good solution for microsecond tuning speeds. Faster tunable devices, in nanosecond tuning speeds, might emerge out of microresonators, electrooptic filters, and active DBR filters.

We propose and demonstrate a new method of optical code-division multiple access (CDMA) based on self-heterodyne filtering. As compared to most CDMA systems, low spectrum spreading is required, thus enabling longer reach transmission capability.

Blind channel estimation is critical for digital signal processing (DSP) compensation of optical fiber communications links. The overall channel consists of deterministic distortions such as chromatic dispersion, as well as random and time varying distortions including polarization mode dispersion and timing jitter. It is critical to obtain robust acquisition and tracking methods for estimating these distortions effects, which, in turn, can be compensated by means of DSP such as Maximum Likelihood Sequence Estimation (MLSE). Here, a novel blind estimation algorithm is developed, accompanied by inclusive mathematical modeling, and followed by extensive set of real time experiments that verify quantitatively its performance and convergence. The developed blind channel estimation is used as the basis of an MLSE receiver. The entire scheme is fully implemented in a 65 nm CMOS Application Specific Integrated Circuit (ASIC). Experimental measurements and results are presented, including Bit Error Rate (BER) measurements, which demonstrate the successful data recovery by the MLSE ASIC under various channel conditions and distances.

STARNET is a broadband backbone optical wavelength-division multiplexing (WDM) local area network (LAN). Based on a physical passive star topology, STARNET offers all users two logical subnetworks: a high-speed reconfigurable packet-switched data subnetwork and a moderate-speed fix-tuned packet-switched control subnetwork. Thus, STARNET supports traffic with a wide range of speed and continuity characteristics. We report the analysis and implementation of an entire STARNET two-node network, from the optical to the computer layer, at the Optical Communications Research Laboratory (OCRL) of Stanford University. To implement the two logical subnetworks, we designed and implemented two different techniques: combined modulation and multichannel subcarrier multiplexing (MSCM). OCRL has already demonstrated several combined modulation techniques such as phase shift-keyed and amplitude shift-keyed (PSK/ASK), and differential phase shift-keyed and amplitude shift-keyed (DPSK/ASK), yielding combined ASK/DPSK modulation receiver sensitivities better than -32 dBm. OCRL has designed and implemented a high-speed high-performance packet-switched STARNET computer interface which enables high-throughput transfer to/from host computer, low latency switching, traffic prioritization, and capability of multicasting and broadcasting. With this interface board, OCRL has achieved average transmit and receive throughputs of 685 Mb/s and 571 Mb/s, respectively, out of the 800 Mb/s theoretical maximum of the host computer bus. The incurred packet latency due to the interface for a specified multihop network configuration has been simulated to be 24 /spl mu/s. Using simulation and experimental results, it is shown that STARNET is highly suitable for high-speed multimedia network applications.