A General Rate K/N Convolutional Decoder Based on Neural Networks with Stopping Criterion

In this paper, carrier multiplexing generalized space shift keying (CM-GSSK) transmission scheme with low decoding complexity is proposed for multiple-input multiple-output (MIMO) systems, using quadrature carriers to increase the spectral efficiency. The CM-GSSK transmission scheme allows two antennas to be active during the same time slot, where the information is conveyed only by the transmit-antenna index. In CM-GSSK transmission scheme, each antenna transmits quadrature carriers, whereas conventional generalized space shift keying (GSSK) transmits the same radio frequency carrier pulse. Unlike a traditional linear decorrelator which is designed for MIMO receiver, a low complexity linear decorrelator based decoder for CM-GSSK scheme is presented and its performance is analyzed. At the receiver, the linear decorrelator decouples the received signal, which in turn, it significantly reduces the decoding complexity. The bit error rate (BER) performance results and the complexity of the proposed low complexity decoding scheme is compared with the baseline SSK schemes to demonstrate its efficiency.

A new rate 1/2 turbo code with short memory 2 is developed in this paper. The proposed turbo code consists of two 4-state parallel concatenated non-punctured systematic rate-2/3 convolutional codes. Using a modified maximum a posteriori (MAP) decoding algorithm working on dual codes, its bit error rate (BER) performance is comparable to that of the classic 16-state turbo code at short block lengths, such as k=1024, while its decoding complexity is less than 1/8 that of the classic 16-state turbo codes; for information block length k=504, its BER performance is better than that of the (1008, 3, 6) LDPC codes with comparable decoding complexity. The dual code decoding algorithm is intrinsically partial parallel and a considerably higher throughput of the turbo decoder can be obtained compared with classic turbo codes consisting of punctured codes. The simulation results show that the proposed turbo code can be a competitive technique for short block length applications.

Space-Division Multiple Access-OFDM based wireless communication has the potential to significantly increase the spectral efficiency, system performance and number of users. Research in the development of efficient multiuser signal detection algorithms for such systems has generated much interest in recent years. This research proposes MUD schemes utilizing three neural network (NN) models like Feed Forward NN (FNN) without any hidden layer, FNN with a single hidden layer and Recurrent Neural Network (RNN) as possible alternatives to existing Genetic Algorithm (GA) based Minimum Bit Error Rate (MBER) MUD. Further, these techniques offer low complexity. Extensive simulation based performance study is carried out to prove the efficiency of the proposed techniques. Better performance of FNN with hidden layer and RNN compared to FNN without hidden layer is clearly observed in rank deficient MIMO scenario, where number of users exceeds the number of receiving antennas. The Bit Error Rate (BER) and complexity analysis of the proposed neural MUD schemes are close to optimal ML and show improvement over the previous implemented technique.

A turbo receiver combined with CFO compensation in frequency-domain for OFDMA uplink

The combination of orthogonal frequency division multiplexing (OFDM) and interleave division multiple access (IDMA), known as OFDM-IDMA, has been proposed as a promising multiple access scheme for wireless communications due to its low decoding complexity and potential of achieving high spectral efficiency. However, most of the work on OFDM-IDMA is in radio frequency (RF) communications scenarios and based on computer simulations. In this paper, we propose OFDM-IDMA over underwater acoustic (UWA) channels with experimental results. We also extend the original OFDM-IDMA to a multiple hydrophones scenario to improve the bit error rate (BER) performance. Experimental results show that with multiple hydrophones, the coded BER performance of OFDM-IDMA approaches zero after only a few iterations, validating the feasibility of our proposed approach over UWA channels.

Since the existing full-rate cooperative transmission schemes have a serious defect in low Bit Error Rate (BER) performance while the existing high-rate cooperative transmission schemes have a serious defect in low spectral efficiency, a distributed high-rate cooperative relay transmission scheme based on full-rate cooperative communication model is proposed in this paper, in which Cyclic Delay Diversity (CDD) technology and Linear Constellation Precoding (LCP) technology are employed. Moreover, the proposed scheme addresses the issue of obtaining maximum spatial and multipath diversity with low decoding complexity and high transmission reliability. The BER performance of the proposed scheme is contrasted to that of the full-rate transmission scheme where better performance is achieved, and is improved when the number of the multipath or the relay nodes increases.

This paper aims at the improvement of the transmission performance of the differential detection system in the mobile radio transmission channel in a frequency selective environment. The multiple differential detection with adaptive sequence estimation (MDD‐ASE) is proposed, and the performance is analyzed by a computer simulation. In MDD‐ASE, not only the differential detection by one‐symbol delay but also the differential detection by two‐ or more‐symbol delays are applied. The soft decision is applied to the output of the multiple differential detection, and the symbol sequence is estimated by Viterbi algorithm (VA). The bit error rate (BER) performance is improved by the extended observation time by the multiple differential detection and the sequence estimation. The number of states in VA and the processing complexity of the adaptive algorithm increases exponentially with the extension of the observation time. Consequently, the following method is proposed: (i) the number of parameters to be estimated is reduced; and (ii) the sequence candidates stored in each path of VA are fed back. In this paper, the configuration and operation of MDD‐ASE are described first and then the transmission performance of the 40 kbit/s QPSK modulation system is presented. As a result of analysis for the static and the dynamic performances of ADD‐MSE using one‐ and two‐symbol differential detection, it is shown that the improvement effect is almost the same as in coherent detection DFE.

In this paper, we propose a novel peak to average power ratio (PAPR) reduction scheme of orthogonal frequency division multiplexing (OFDM) signals. In our proposed scheme we exploit the repeated rotation and recombination of the in-phase and the quadrature components of an OFDM symbol in time domain. Our proposed scheme has two main advantages over the previously known scheme such as iterative partial transmit sequence (I-PTS), which are 1) remarkably lower computational complexity and 2) less required side information overhead than the I-PTS scheme. Based on our derived complementary cumulative distribution (CCDF) of PAPR, we show that our proposed scheme gives only 0.2 - 0.3 dB loss compared to the I-PTS scheme in terms of PAPR threshold while the complexity for the implementation is much reduced. Furthermore, the proposed scheme does not cause any loss of bit error rate performance over both the additive white Gaussian noise (AWGN) channel and the frequency selective channel even though the simulation results regarding the bit error rate (BER) performance is not shown in this paper due to the limited space of the pages.

Joint data and channel estimation for mobile communication receivers can be realized by employing a Viterbi detector along with channel estimators which estimate the channel impulse response. The behavior of the channel estimator has a strong impact on the overall error rate performance of the receiver. Kalman filtering is an optimum channel estimation technique which can lead to significant improvement in the receiver bit error rate (BER) performance. However, a Kalman filter is a complex algorithm and is sensitive to roundoff errors. Square-root implementation methods are required for robustness against numerical errors. Real-time computation of the Kalman estimator in a mobile communication receiver calls for parallel and pipelined structures to take advantage of the inherent parallelism in the algorithm. In this paper different implementation methods are considered for measurement update and time update equations of the Kalman filter. The unit-lower-triangular-diagonal (LD) correction algorithm is used for the time update equations, and systolic array structures are proposed for its implementation. For the overall implementation of joint data and channel estimation, parallel structures are proposed to perform both the Viterbi algorithm and channel estimation. Simulation results show the numerical stability of different implementation techniques and the number of bits required in the digital computations with different estimators.

The space-based automatic identification system (AIS) has attracted much attention because the system can receive AIS signals from ships on the high seas. As its serious problem, multiple AIS packets can collide at one satellite because it has a wide coverage area. Parallel interference cancellation (PIC) based on Viterbi algorithm (VA) is very effective in separating the collided packets and shows an excellent bit error rate (BER) performance under the condition that Doppler frequencies, channel impulse responses, and propagation delay time are ideally estimated. When the estimation of those channel parameters is not sufficiently accurate with desired to undesired signal power ratio (DUR) being low, however, the BER of PIC can be seriously degraded. In this paper, we propose a novel iterative channel estimation scheme for each channel parameter to improve the estimation accuracy even under the low DUR condition. The least squares and quasi-Newton methods are applied to the estimation of the channel impulse responses and Doppler frequencies, respectively, besides coarse estimation using correlators. The correlation-based estimation of the propagation delay time is repeated. Computer simulations demonstrate that the proposed scheme can estimate the channel parameters more accurately, which leads to remarkable improvement in the BER performance.

Ultra Wide Band (UWB) schemes have become a viable option to meet the demand of high data rate wireless communication. Appealing features such as flexibility and robustness, as well as high precision ranging capability, have polarized attention and made UWB an excellent candidate for variety of applications. There are many communications scenarios where multiple wideband transmissions in the same radio channel may exist. The resulting co-channel interference (CCI) from multiple user devices is taken into consideration. CCI is a degrading phenomenon and it deteriorates the quality of desired communication link. Artificial Neural Network (ANN) as non parametric pattern mapping tool can tackle time varying nature of UWB setup while carrying out channel modeling and estimation. The Recurrent Neural Network (RNN) being dynamic ANN have better time tracking capability. The temporal characteristics of RNN along with Decision Feedback Equalization (DFE) are used in the proposed work. A hybrid approach using RNN and DFE is formulated which is able to satisfactorily mitigate the CCI effects, lower the bit error rate (BER) and better tracking capability in UWB framework.

To improve the bit error rate (BER) performance of multiple input multiple output (MIMO) systems with low complexity, a three-branch transmission scheme employing 8-weighted-type fractional Fourier transform (8-WFRFT) module is proposed. In the proposed scheme, the original signal is first decomposed into eight sub-signals and then merged into three component signals by the same carrier pattern. The three signals have mathematical constraint relations among themselves that can counteract the channel fading. They are simultaneously transmitted via three independent antennas after delay regulating. At the receiver, an inverse 8-WFRFT module is employed to obtain the estimated original signal by processing the received signal. Then, the bit error rate (BER) performance, transmitting power, transmission rate, power spectrum and computational complexity of the proposed scheme are analysed in detail. Numerical results show that the proposed scheme has a superior performance compared to STBC based three-antenna transmission scheme, in terms of BER performance.

This paper considers the bit error rate (BER) performance of the 3GPP WCDMA-FDD system with space-time transmit diversity in the indoor environments by employing a resolution-reduced maximum ratio combing (RR-MRC) RAKE receiver. An average uncoded BER lower bound is used for the BER performance analysis, which is based on a proper complex Gaussian (PCG) multichannel assumption without inter-symbol interference (ISI). Numerical results show that substantial diversity diversity gain can still be obtained with the suboptimal RR-MRC receiver even in a mixed-mode fading multipath channel with the rms delay spread around 50 nanoseconds.

In this letter, we investigate the idea of interference spreading and its effect on bit error rate (BER) performance in a cognitive radio network (CRN). The interference spreading phenomenon is caused because of the random allocation of subcarriers in an orthogonal frequency division multiplexing (OFDM)-based CRN without any spectrum-sensing mechanism. The CRN assumed in this work is of underlay configuration, where the frequency bands are accessed concurrently by both primary users (PUs) and secondary users (SUs). With random allocation, subcarrier collisions occur among the carriers of primary users (PUs) and secondary users (SUs), leading to interference among subcarriers. This interference caused by subcarrier collisions spreads out across multiple subcarriers of PUs rather than on an individual PU, therefore avoiding high BER for an individual PU. Theoretical and simulated signal to interference and noise ratio (SINR) for collision and no-collision cases are validated for M-quadrature amplitude modulation (M-QAM) techniques. Similarly, theoretical BER performance expressions are found and compared for M-QAM modulation orders under Rayleigh fading channel conditions. The BER for different modulation orders of M-QAM are compared and the relationship of average BER with interference temperature is also explored further.

The paper offers a design of an optical non-orthogonal multiple access (O-NOMA) system with Rayleigh fading channels by analysing the bit error rate (BER) and power spectral density (PSD) using machine learning (ML)-based and traditional signal detection methods. The primary focus is on various QAM modulation orders, such as 32-QAM, 64-QAM, 256-QAM, and 512-QAM. The research compares the performance of different detectors including deep neural networks (DNN), convolutional neural networks (CNN), recurrent neural networks (RNN), and conventional techniques. Among these, the DNN always yields better BER performance up to 10−5 BER at SNR values 12 dB lower than conventional techniques. For 32-QAM, in particular, the DNN provides a gain of 10.3 dB compared to conventional techniques, while similar gains are realized for higher QAM orders. PSD analysis also shows that the DNN is compact in terms of its spectral footprint, achieving out-of-band emissions as low as −690 dB, essential for reducing interference and maximizing spectral efficiency. Such results highlight the promise of using ML-based detection – particularly DNN – as an efficient and effective method for future, high-capacity optical NOMA systems functioning over a wide range of modulation schemes.