Symbol-by-symbol Research Articles

Analysis of Low Probability of Detection Capability for Chaotic Standard Map-Based FH-OFDMA System

A frequency hopping orthogonal frequency division multiple access (FH-OFDMA) can provide low probability of detection (LPD) and anti-jamming capabilities to users against adversary detectors. To obtain an extreme LPD capability that cannot be provided by the basic symbol-by-symbol (SBS)-based FH pattern, we proposed two FH patterns, namely chaotic standard map (CSM) and cat map for FH-OFDMA systems. In our previous work, through analysis of complexity to regenerate the transmitted symbol sequence, at the point of adversary detectors, we found that the CSM had a lower probability of intercept than the cat map and SBS. It is possible when a detector already knows symbol and frame structures, and the detector has been synchronized to the FH-OFDMA system. Unlike the previous work, here, we analyze whether the CSM provides greater LPD capability than the cat map and SBS by detection probability using spectrum sensing technique. We analyze the detection probability of the CSM and provide detection probabilities of the cat map and SBS compared to the CSM. Based on our analysis of the detection probability and numerical results, it is evident that the CSM provides greater LPD capability than both the cat map and SBS-based FH-OFDMA systems.

Linguistic and temporal resources of pre-stored utterances in everyday conversations

Aided communicators often have an opportunity to express themselves with speech-generating devices (SGDs) that produce symbol by symbol (SBS) and/or pre-stored (PS) utterances. Studies on the usage of PS utterances report that these utterances affect conversations positively, but it appears that aided communicators and professionals may have divergent views on their benefits. The aim of this study is to analyse how school-aged aided communicators, their mothers, peers, and speech and language therapists (SLTs) co-construct the social actions of PS utterances during their everyday interactions. The theoretical framework of this study is conversation analysis. This approach to analysing the data enhances our understanding of the linguistic and temporal resources of PS utterances and how they are used to reinforce various rich social actions that promote the progress of aided conversations to resemble natural spoken conversations. The results of this study will help SLTs and teachers in their planning content for SGDs as well as in teaching, and guiding aided communicators and their partners to utilize PS utterances in combination with SBS utterances during their conversations.

Non-Coherent Detection for Diffusive Molecular Communication Systems

We study non-coherent detection schemes for molecular communication (MC) systems with negligible inter-symbol interference that do not require knowledge of the channel state information (CSI). In particular, we first derive the optimal maximum likelihood (ML) multiple-symbol (MS) detector for MC systems. As a special case of the optimal MS detector, we show that the optimal ML symbol-by-symbol (SS) detector can be equivalently written in the form of a threshold-based detector, where the optimal decision threshold is constant and depends only on the statistics of the MC channel. The main challenge of the MS detector is the complexity associated with the calculation of the optimal detection metric. To overcome this issue, we propose an approximate MS detection metric that can be expressed in closed form. In addition, we develop a non-coherent decision-feedback detector, which introduces a lower detection delay compared with the optimal MS detector, and a suboptimal blind detector, which has a significantly lower complexity than the optimal MS detector. Finally, we derive analytical expressions for the bit error rate (BER) of the optimal SS detector, as well as upper and lower bounds for the BER of the optimal MS detector. Simulation results confirm the analysis and reveal the effectiveness of the proposed optimal and suboptimal detection schemes compared with the benchmark scheme that assumes perfect CSI knowledge, particularly, when the number of observations used for detection is sufficiently large. Simulation results are also presented that show the performance of the proposed detectors, when inter-symbol interference is non-negligible.

Stochastic Digital Backpropagation With Residual Memory Compensation

Stochastic digital backpropagation (SDBP) is an extension of digital backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP takes into account noise from the optical amplifiers in addition to handling deterministic linear and nonlinear impairments. The decisions in SDBP are taken on a symbol-by-symbol (SBS) basis, ignoring any residual memory, which may be present due to non-optimal processing in SDBP. In this paper, we extend SDBP to account for memory between symbols. In particular, two different methods are proposed: a Viterbi algorithm (VA) and a decision directed approach. Symbol error rate (SER) for memory-based SDBP is significantly lower than the previously proposed SBS-SDBP. For inline dispersion-managed links, the VA-SDBP has up to 10 and 14 times lower SER than DBP for QPSK and 16-QAM, respectively.

Orthogonal Space-Time Block Codes in Vehicular Environments: Optimum Receiver Design and Performance Analysis

We consider orthogonal space-time block codes (OSTBC) in vehicular environments, where the channels are nonidentically distributed. It is shown that the nonidentical channel statistics lead to nonidentical channel estimation errors, which consequently affect the performance and even the existing receiver structure of OSTBC. We show that the conventional symbol-by-symbol (SBS) decoder of OSTBC is suboptimum in vehicular environments. A new optimum decoder is derived, which can be simplified to a new SBS decoder under certain conditions. To the best of our knowledge, our work here is the first to consider the optimum decoder for OSTBC in vehicular environments. Performance analysis and simulations are provided, which show that our new decoder substantially outperforms the conventional decoder.

An adaptive coherent receiver for MPSK/MDPSK over the nonselective Rayleigh fading channel with unknown characteristics

A coherent symbol-by-symbol (SBS) diversity receiver for m-ary phase-shift keying (MPSK) and differentially encoded MPSK (MDPSK) signals transmitted over a nonselective Rayleigh fading channel is presented. It incorporates a new adaptive filter for channel estimation that does not require any prior knowledge of the fading process model. It estimates the fading gains through decision-feedback and recursive least squares adaptation of the filter coefficients. A novel forgetting-factor adaptation algorithm that enables the filter to react quickly to randomly changing fading statistics caused by shadowing and acceleration/deceleration is introduced. Simulations show that the receiver performs better than that of Adachi's ( IEEE Trans. Veh. Technol. vol. 47 p. 909, 1998), either without shadowing or under slow lognormal shadowing.

Performance of a nonlinear adaptive SBS-MAP detector using soft-statistics for digital transmissions over HF channels

The effectiveness of the adaptive maximum a posteriori (MAP) receiver in Cusani and Mattila is verified for digital HF links between mobile and/or fixed units. Following Cusani and Mattila (1998), a suitable MAP algorithm is employed to compute symbol-by-symbol (SBS) the a posteriori probabilities (APPs) of the channel state; from these, the detected data stream is obtained. The same APPs are employed by an adaptive nonlinear Kalman-like filter to estimate recursively the time-varying channel with fast convergence and good tracking properties, overcoming the delay problem suffered by conventional adaptive MLSE-VA detectors. Computer simulations allow to compare the adaptive SBS-MAP with other receivers (DFE, MLSE) and verify its effectiveness in the HF environment.

An approach based on soft-statistics to the joint adaptive equalization/decoding of TCM data for multipath channels

Adaptive detection based on soft-statistics of Trellis-Coded-Modulated (TCM) data transmitted over multipath-degraded fast time-variant channels is considered. Starting from some system-considerations about the equalization/decoding of multipath radio mobile links, a fast-adaptive receiver suitable for cellular applications is presented where the tasks of channel-estimation, equalization and decoding are carried out in a combined optimized form. The last two operations are jointly accomplished by a Symbol-by-Symbol (SbS) Maximum A posteriori Probability (MAP) detector which delivers soft-statistics in the form of suitably defined A Posteriori Probabilities (APPs). These APPs are used for channel-estimation so that the resulting channel-estimator is optimal (in a Minimum Mean Square Error (MMSE) sense) and is able to exploit the redundancy introduced by the code. As a matter of fact, it exhibits an enhanced tracking capability when the impulse-response of the channel is fast time-variant.

Combined channel estimation and data detection using soft statistics for frequency-selective fast-fading digital links

A novel adaptive nonlinear equalizer for fast time-varying multipath channels that combines the channel estimation and data detection tasks is presented. The a posteriori probabilities (APPs) of the states of the intersymbol interference (ISI) channel are recursively computed from the received data by a symbol-by-symbol (SbS) detector and are then employed by a Kalman-type nonlinear channel estimator. Robust channel tracking and good data-detection performance are obtained, with a reasonable receiver complexity.

New results about analysis and design of TCM for ISI channels and combined equalization/decoding

New upper bounds for the performance of the optimum combined symbol-by-symbol (SbS) Abend-Fritchman-like equalizer and decoder are presented, and a related criterion for the actual design of good trellis-coded-modulated (TCM) schemes effectively matched to the distortion introduced by the intersymbol interference (ISI)-corrupted transmission channel is developed. The actual application of the proposed design criterion is also addressed.

Performance bound and trellis-code design criterion for discrete memoryless channels and finite-delay symbol-by-symbol decoding

A new tight analytical upper bound is presented for the performance of finite-delay symbol-by-symbol (SBS) Abend-Fritchman-like decoding of trellis-encoded data crossing arbitrary (eventually time-varying) discrete memoryless channels (DMCs). On the basis of this bound, a related criterion for the optimal design of trellis codes with SBS decoding is then proposed. It gives rise to an effective procedure for the construction of good trellis codes (generally time varying and nonlinear) with assigned decoding complexity.

Algorithm for SBS receivers/decoders

An efficient algorithm for symbol-by-symbol (SBS) receivers/decoders is presented. Its memory and computational requirements compare favourably with those of the existing SBS decoders. The algorithm is formulated using a simple and compact matrix notation.