Carrier Multiple Access Research Articles

An Approach Towards Automate Models Construction and Research of Wireless Local Area Networks based on State Transition Diagram

Wireless Local Area Networks (WLANs) are widely used and their number is constantly increasing. Therefore, the creation of models for their detailed study, and even more, so the automation of this process is an urgent task. As an example of the research object, we chose the Media Access Control (MAC) sublayer and the Carrier Multiple Access with Collision Avoidance (CSMA/CA) access scheme. A simplified version of the state transition diagram was suggested by us, and an analytical model based on a system of differential equations was developed. Automation of the process of creating such models is realized by a software solution developed to automate the construction of analytical models of any objects described by a state transition diagram. The program automatically constructs and solves a system of differential equations using the substitution method, as well as constructs state diagrams.

Blind estimation of modulation parameters for PCMA signals using frame cyclic features

Blind receiver technologies for paired carrier multiple access (PCMA) signals have always been a challenging task with many technical difficulties, among which the estimation of modulation parameters is a fundamental but important element. Despite some achievements in previous studies, more systematic and sophisticated estimation methods have not been adequately investigated. In this paper, schemes for the blind estimation of the symbol timing phase, amplitude attenuation, frequency offset, and carrier phase for PCMA signals in satellite communications are proposed. The data flow transmitted in satellite communication often has a certain frame structure, the most important of which is the synchronization data, namely the so-called cycle features. The proposed schemes assume that the modulated signals have fixed frame length and frame sync code and that the symbol rate has been estimated when the signals are encoded asynchronously. Distinct from the previous methods, our schemes exploit the sync waveform and the overlapping waveform, which are estimated via singular value decomposition (SVD) (using the frame cyclic features) and interference cancelation, together with their demodulation results as aid data, for the estimation of the desired parameters. The simulation results demonstrate that the schemes are effective in the parameters estimation of PCMA signals and outperform the comparison algorithms.

Investigations on PAPR and SER Performance Analysis of OFDMA and SCFDMA under Different Channels

Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing are two multicarrier regulatory systems that have improved due to the growing demand in quick communication (OFDM). A frequency division multiplexing (FDM) plot called orthogonal frequency division multiplexing is utilized as a sophisticated multi carrier regulation approach.
 Due to its excellent spectrum efficiency and low data rate, the single carrier multiple access system (SC-FDMA) is a unique radio transmission technique that is now employed in long-term evolution (LTE) technology for uplink. When compared to OFDM, reduced peak-to-average power ratio (PAPR) and error rate technique. PAPR performance has been obtained using Matlab simulation. Techniques using variable numbers of subcarriers include SC-FDMA and OFDMA. Two various subcarrier assignment strategies have been proposed, distributed FDMA Localized FDMA and (DFDMA) (LFDMA). IFDMA, or interleaved FDMA, is a DFDMA special situation when DFT results have been distributed consistently and at the same distance. When comparing the SC-FDMA variants, we discover that Localized has a higher PAPR than interleaved (FDMA) (FDMA). We also talk about the Performance of LFDMA and IFDMA's SER (Symbol Error Rate) and found that localized (FDMA) performs better in the SER than interleaved (IFDMA) method.

Investigations on PAPR and SER Performance Analysis of OFDMA and SCFDMA under Different Channels

Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing are two multicarrier regulatory systems that have improved due to the growing demand in quick communication (OFDM). A frequency division multiplexing (FDM) plot called orthogonal frequency division multiplexing is utilized as a sophisticated multi carrier regulation approach.
 Due to its excellent spectrum efficiency and low data rate, the single carrier multiple access system (SC-FDMA) is a unique radio transmission technique that is now employed in long-term evolution (LTE) technology for uplink. When compared to OFDM, reduced peak-to-average power ratio (PAPR) and error rate technique. PAPR performance has been obtained using Matlab simulation. Techniques using variable numbers of subcarriers include SC-FDMA and OFDMA. Two various subcarrier assignment strategies have been proposed, distributed FDMA Localized FDMA and (DFDMA) (LFDMA). IFDMA, or interleaved FDMA, is a DFDMA special situation when DFT results have been distributed consistently and at the same distance. When comparing the SC-FDMA variants, we discover that Localized has a higher PAPR than interleaved (FDMA) (FDMA). We also talk about the Performance of LFDMA and IFDMA's SER (Symbol Error Rate) and found that localized (FDMA) performs better in the SER than interleaved (IFDMA) method.

Low-Complexity Self-Interference Cancellation for Multiple Access Full Duplex Systems.

Self-interference occurs when there is electromagnetic coupling between the transmission and reception of the same node; thus, degrading the RX sensitivity to incoming signals. In this paper we present a low-complexity technique for self-interference cancellation in multiple carrier multiple access systems employing whole band direct to digital sampling. In this scenario, multiple users are simultaneously received and transmitted by the system at overlapping arbitrary bandwidths and powers. Traditional algorithms for self-interference mitigation based on recursive least squares (RLS) or least mean squares (LMS), fail to provide sufficient rejection, since the incoming signal is far from being spectrally flat, which is critical for their performance. The proposed algorithm mitigates the interference by modeling the incoming multiple user signal as an autoregressive (AR) process and jointly estimates the AR parameters and self-interference. The resulting algorithm can be implemented using a low-complexity architecture comprised of only two RLS modules. The novel algorithm further satisfies low latency constraints and is adaptive, supporting time varying channel conditions. We compare this to many self-interference cancellation algorithms, mostly adopted from the acoustic echo cancellation literature, and show significant performance gain.

Distributed SC-FDMA sub-carrier assignment for digital mobile satellite

Single carrier multiple access division (SC-FDMA) technology is one of the good uplink modulation techniques in a wireless communication system. Promises high transmission speed, low bit error rate and high spectral efficiency with low peak to average power ratio (PAPR) compared to OFDMA. This paper is proposed analytical model and link level simulation using MATLAB® to enhance the ratio of peak average power (PAPR) performance for distributed SC-FDMA sub-carrier assignment of. The methodology using the first full-featured digital MIMO software allows for in-depth verification and improvement of MIMO technologies applied to satellite broadcasting networks. Moreover, the demonstrator allows to complete and confirm our theory and simulation-based. The aim of this paper is to enhancement PAPR by analyzing the mobile satellite digital that employed distributed sub-carrier assignment for MIMO-SC-FDMA. The model is verified and validated by link level simulation.

Blind separation of noncooperative paired carrier multiple access signals based on improved quantum‐inspired evolutionary algorithm and receding horizon optimization

AbstractThe single‐channel blind source separation of paired carrier multiple access (PCMA) signal is a key technology in satellite communications. Due to the high‐order complexity of existing separation methods and the uncertainty of channel parameters, the processing of noncooperative PCMA signals with long memory remains a great challenge. In this article, the blind separation was solved as the joint channel estimation and sequence detection, and a novel blind separation algorithm based on the improved quantum‐inspired evolutionary algorithm (IQEA) and receding horizon optimization was proposed. Considering the practical scenarios, a mixed PCMA signal model with noninteger period sampling was presented in advance. Combined with the proposed signal model, the IQEA was applied to recover the uplink signals from the mixed PCMA signals by its iterative estimation. Meanwhile, to reduce the computational complexity caused by long memory of PCMA signals, the receding horizon optimization was introduced to process the whole signal sequence as a dynamic programming problem. The simulation results verified that the proposed RH‐IQEA outperforms existing state‐of‐the‐art separation algorithms in the blind separation of noncooperative PCMA signals, with higher accuracy, lower‐order complexity and stronger robustness to parameter estimation errors.

Research on Satellite Concealment Communication Method Based on WFRFT

Satellite signal concealment technology protects the safety of signal waveform by using signals with high power and specific parameter characteristics. However, with the development of modulation recognition and Successive Interference Cancellation (SIC) technology, the cover signal using conventional modulation methods can be cracked by non-cooperative receivers. In order to meet the safety communication requirements of portable satellite communication terminals, the idea of using local signal copies for self-interference cancellation in Paired Carrier Multiple Access (PCMA) is used for reference. This paper proposes a satellite secure communication method suitable for portable terminals, and introduces Weighted-type FRactional Fourier Transform (WFRFT) as a modulation method to mask the signal, thereby increase the difficulty of non-cooperative parties in identifying and demodulating the cover signal. Simulation shows that the method proposed in this paper improves the security of signal transmission, and the loss of the system's bit error rate is within an acceptable range after signal separation, which is suitable for practical use.

Joint Blind Parameter Estimation of Non-cooperative High-Order Modulated PCMA Signals

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.

Single‐channel blind source separation for paired carrier multiple access signals

Paired carrier multiple access (PCMA) is one of the most common single-channel mixtures. It is still a great challenge to recover the transmitted bits from non-cooperative received PCMA signals, due to the high complexity of existing single-channel blind source separation (SCBSS) algorithms. Hence, a double-direction delayed-decision-feedback sequence estimation (DD-DDFSE) algorithm for non-causal high-order channel is proposed to realise the separation of PCMA signals. The proposed algorithm employs the Viterbi algorithm (VA) with low-order channel twice instead of conventional VA with high-order channel once. The symbols estimated by the initial VA are utilised to equalise the causal and non-causal taps of the channel beyond the trellis state in the second VA. The relationship between the decision-feedback error from the initial VA and the performance of the second VA is also derived. Compared with state-of-the-art maximum likelihood sequence estimation algorithms, DD-DDFSE algorithm can not only decrease the computation complexity but also improve the separation performance.

Blind separation of PCMA signals based on neural network

For paired carrier multiple access (PCMA) signals, a new single-channel blind separation on neural network was proposed. Firstly, the sample waveforms (three symbols) which contains different bit information are constructed, secondly, the time-frequency spectrum of each sample under the different influences of the trailing symbols is Intercepted, finally, the characteristic data of the spectrum as the input data, and the two-bit sequence in each sample as the output data to be trained, network trains these data repeatedly to complete the construction of separation model. The receiver carries on window truncation to the time-frequency spectrum of PCMA signal, neural network recognize the characteristic data of these spectrums to realizes the separation of bit sequences. Experimental results show that this algorithm has lower complexity than PSP algorithm, and the accuracy of it is close to PSP algorithm (L=5).

More general performance evaluation for single‐channel PCMA signals blind separation

The single-channel blind separation performance of the mixed signals with parameters estimation error in paired carrier multiple access (PCMA) satellite communication systems is analysed in this study. Current literatures have theoretically analysed the blind separation performance using the symbol detection error probability of PCMA signals. However, the parameters of PCMA signals are assumed to be accurate during their derivations, which are not practical in blind separation scenario. In this study, the parameters' estimation error is considered during the derivation of the blind separation performance of PCMA signals. Thus, the derived performance is more general. The simulation separation result is obtained by per-survivor processing method. It is in accordance with the derived performance.

Markov Chain Monte Carlo-Based Separation of Paired Carrier Multiple Access Signals

Paired carrier multiple access (PCMA) signal is one of the most common single-channel mixtures. It is still a great challenge to recover the component signals from non-cooperative received PCMA signals due to the high complexity of existing single-channel blind source separation algorithms. Hence, a Markov chain Monte Carlo (MCMC) procedure, called the QR Decomposition with M algorithm-based Gibbs sampler, is employed to realize the separation of PCMA signals. The method is robust against modulation parameter estimation error, since a data-aided adaptive filter that can update the channel response is embedded into the QRD-M-based Gibbs sampler. Simulation results show that the MCMC estimator efficiently achieves approximately joint likelihood sequence estimation.

The DFF‐PSP Iterative Separation and Theoretical Bound for PCMA with Long Memory

This paper proposes the Decision feedbackfeedforward per-survivor processing (DFF-PSP) iterative separation algorithm and the Monte Carlo integrationbased method to compute the theoretical bound for Paired carrier multiple access (PCMA) Single channel blind separation (SCBS) which is highly complex with long memory. The truncated PSP is employed while the pre- and post- cursors are disregarded to control the complexity. The delayed decisions feedforward and local decisions feedback filters are designed to process the pre- and post- cursors. The Bit-interleaved code modulation iterative decoder (BICM-ID) is combined with the second soft decision of the truncated PSP to obtain a better performance. The mixture signal model is regarded as a Multiple-access channel (MAC) with memory, and the theoretical performance bound is obtained via entropy inequality, Monte Carlo integration and Fano inequality. Simulation results show that the DFF-PSP iterative separation provides the good tradeoff between complexity and performance.