Influence of Behavioral Models on Multiuser Channel Capacity

In order to characterize the channel capacity of a wavelength channel in a wavelength-division multiplexed (WDM) system, statistical models are needed for the transmitted signals on the other wavelengths. For example, one could assume that the transmitters for all wavelengths are configured independently of each other, that they use the same signal power, or that they use the same modulation format. In this paper, it is shown that these so-called behavioral models have a profound impact on the single-wavelength achievable information rate. This is demonstrated by establishing, for the first time, upper and lower bounds on the maximum achievable rate under various behavioral models, for a rudimentary WDM channel model

High performance faster-than-nyquist signaling

AbstractIn a wireless broadband context, multi-path dispersive channels can severely affectdata communication of Mobile Terminals (MTs) uplink.Single Carrier withFrequency-Domain Equalization (SC-FDE) has been proposed to deal with highlydispersive channels for the uplink of broadband wireless systems. However, currentsystems rely on older assumptions of the Nyquist theorem and assume that a systemneeds a minimum bandwidth 2Wper MT. Faster-Than-Nyquist (FTN) assumesthat it is possible to employ a bandwidth as low as 0.802 of the original Nyquistbandwidth with minimum loss - despite this, the current literature has only proposedcomplex receivers for a simple characterization of the wireless channel. Furthermore,the uplink of SC-FDE can be severely affected by a deep-fade and or poor channelconditions; to cope with such difficulties Diversity Combining (DC) Hybrid ARQ(H-ARQ) is a viable technique, since it combines the several packet copies sent bya MT to create reliable packet symbols at the receiver.In this thesis we consider the use of FTN signaling for the uplink of broadbandwireless systems employing SC-FDE based on the Iterative Block with DecisionFeedback Equalization (IB-DFE) receiver with a simple scheduled access HybridAutomatic Repeat reQuest (H-ARQ) specially designed taking into account thecharacteristics of FTN signals. This approach achieves a better performance thanNyquist signaling by taking advantage of the additional bandwidth employed of aroot-raised cosine pulse for additional diversity.Alongside a Packet Error Rate (PER) analytical model, simulation results show that this receiver presents a better performance when compared with a regular system,with higher system throughputs and a lower Energy per Useful Packet (EPUP)

Capacity of a Nonlinear Optical Channel with Finite Memory

The channel capacity of a nonlinear, dispersive fiber-optic link is revisited. To this end, the popular Gaussian noise (GN) model is extended with a parameter to account for the finite memory of realistic fiber channels. This finite-memory model is harder to analyze mathematically but, in contrast to previous models, it is valid also for nonstationary or heavy-tailed input signals. For uncoded transmission and standard modulation formats, the new model gives the same results as the regular GN model when the memory of the channel is about 10 symbols or more. These results confirm previous results that the GN model is accurate for uncoded transmission. However, when coding is considered, the results obtained using the finite-memory model are very different from those obtained by previous models, even when the channel memory is large. In particular, the peaky behavior of the channel capacity, which has been reported for numerous nonlinear channel models, appears to be an artifact of applying models derived for independent input in a coded (i.e., dependent) scenario

Maximum likelihood sequence detection with closed-form metrics in OOK optical systems impaired by GVD and PMD

This paper thoroughly investigates the maximum-likelihood sequence detection (MLSD) receiver for the optical ON-OFF keying (OOK) channel in the presence of both polarization mode dispersion and group velocity dispersion (GVD). A reliable method is provided for computing the relevant performance for any possible value of the system parameters, with no constraint on the sampling rate. With one sample per bit time, a practically exact expression of the statistics of the received samples is found, and therefore the performance of a synchronous MLSD receiver is evaluated and compared with that of other electronic techniques such as combined feedforward and decision-feedback equalizers (FFE and DFE). It is also shown that the ultimate performance of electronic processing can be obtained by sampling the received signal at twice the bit rate. An approximate accurate closed-form expression of the receiver metrics is also identified, allowing for the implementation of a practically optimal MLSD receiver

Digital processing of signals in the presence of inter-symbol interference and additive noise

Imperial Users onl

Joint array combining and MLSE for single-user receivers in multipath Gaussian multiuser channels

The well-known structure of an array combiner along with a maximum likelihood sequence estimator (MLSE) receiver is the basis for the derivation of a space-time processor presenting good properties in terms of co-channel and intersymbol interference rejection. The use of spatial diversity at the receiver front-end together with a scalar MLSE implies a joint design of the spatial combiner and the impulse response for the sequence detector. This is faced using the MMSE criterion under the constraint that the desired user signal power is not cancelled, yielding an impulse response for the sequence detector that is matched to the channel and combiner response. The procedure maximizes the signal-to-noise ratio at the input of the detector and exhibits excellent performance in realistic multipath channels.Peer Reviewe

Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters

Abstract-This paper presents a new kind of adaptive filter: type-2 fuzzy adaptive filter (FAF); one that is realized using an unnormalized type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system (FLS). We apply this filter to equalization of a nonlinear time-varying channel and demonstrate that it can implement the Bayesian equalizer for such a channel, has a simple structure, and provides fast inference. A clustering method is used to adaptively design the parameters of the FAF. Two structures are used for the equalizer: transversal equalizer (TE) and decision feedback equalizer (DFE). A new decision tree structure is used to implement the decision feedback equalizer, in which each leaf of the tree is a type-2 FAF. This DFE vastly reduces computational complexity as compared to a TE. Simulation results show that equalizers based on type-2 FAFs perform much better than nearest neighbor classifiers (NNC) or equalizers based on type-1 FAFs. Index Terms-Channel equalization, decision feedback equalizer, decision tree, interval type-2 TSK fuzzy logic systems, timevarying channels, type-2 fuzzy adaptive filters

Application of wavelets and artificial neural network for indoor optical wireless communication systems

Abstract This study investigates the use of error control code, discrete wavelet transform (DWT) and artificial neural network (ANN) to improve the link performance of an indoor optical wireless communication in a physical channel. The key constraints that barricade the realization of unlimited bandwidth in optical wavelengths are the eye-safety issue, the ambient light interference and the multipath induced intersymbol interference (ISI). Eye-safety limits the maximum average transmitted optical power. The rational solution is to use power efficient modulation techniques. Further reduction in transmitted power can be achieved using error control coding. A mathematical analysis of retransmission scheme is investigated for variable length modulation techniques and verified using computer simulations. Though the retransmission scheme is simple to implement, the shortfall in terms of reduced throughput will limit higher code gain. Due to practical limitation, the block code cannot be applied to the variable length modulation techniques and hence the convolutional code is the only possible option. The upper bound for slot error probability of the convolutional coded dual header pulse interval modulation (DH-PIM) and digital pulse interval modulation (DPIM) schemes are calculated and verified using simulations. The power penalty due to fluorescent light interference (FL I) is very high in indoor optical channel making the optical link practically infeasible. A denoising method based on a DWT to remove the FLI from the received signal is devised. The received signal is first decomposed into different DWT levels; the FLI is then removed from the signal before reconstructing the signal. A significant reduction in the power penalty is observed using DWT. Comparative study of DWT based denoising scheme with that of the high pass filter (HPF) show that DWT not only can match the best performance obtain using a HPF, but also offers a reduced complexity and design simplicity. The high power penalty due to multipath induced ISI makes a diffuse optical link practically infeasible at higher data rates. An ANN based linear and DF architectures are investigated to compensation the ISI. Unlike the unequalized cases, the equalized schemes don‘t show infinite power penalty and a significant performance improvement is observed for all modulation schemes. The comparative studies substantiate that ANN based equalizers match the performance of the traditional equalizers for all channel conditions with a reduced training data sequence. The study of the combined effect of the FLI and ISI shows that DWT-ANN based receiver perform equally well in the present of both interference. Adaptive decoding of error control code can offer flexibility of selecting the best possible encoder in a given environment. A suboptimal ?soft‘ sliding block convolutional decoder based on the ANN and a 1/2 rate convolutional code with a constraint length is investigated. Results show that the ANN decoder can match the performance of optimal Viterbi decoder for hard decision decoding but with slightly inferior performance compared to soft decision decoding. This provides a foundation for further investigation of the ANN decoder for convolutional code with higher constraint length values. Finally, the proposed DWT-ANN receiver is practically realized in digital signal processing (DSP) board. The output from the DSP board is compared with the computer simulations and found that the difference is marginal. However, the difference in results doesn‘t affect the overall error probability and identical error probability is obtained for DSP output and computer simulations