Search

Non-orthogonal multiple access (NOMA) is a key technology for future wireless access. Recently, asynchronous NOMA (ANOMA) has attracted attention due to its large achievable rate. However, almost all work to date on NOMA employs linear modulation formats dedicated to linear amplifiers with low power efficiency. In this paper, we propose an uplink ANOMA scheme based on continuous phase modulation (CPM). In particular, a generalized system model with any number of users, response lengths, and frequency pulses is established, and the traditional ANOMA with linear waveforms (considering the nonlinearity of the power amplifier) is provided as a comparison. Furthermore, the achievable rate of each user and its asymptotic value under successive interference cancellation (SIC) and joint maximum likelihood (JML) detectors are derived respectively, and the achievable sum rates are also given. Numerical results show that the achievable rate converges to its asymptotic value. The nonlinear system can provide a larger achievable rate compared with the linear system. The relationship between the achievable sum rate of nonlinear systems and response length, transmit power, channel gain, frequency pulse, time offset and received signal-to-noise ratio (SNR) between users is also investigated via numerical simulations. [ABSTRACT FROM AUTHOR]

In the recent past, sparse arrays have received significant attention due to their inherent ability of offering increased degrees of freedom (DOFs) along with an enlarged array aperture, compared to uniform linear arrays (ULAs). These attributes are essential to improve the direction-of-arrival (DOA) estimation accuracy. Keeping in view, a new sparse array configuration based on pentad-displaced ULAs (Pdis-ULAs) structure is presented in this paper. The proposed geometry generally consists of five ULAs and a single element placed effectively. Both the intra-ULA sensor placement and the displacement between ULAs, are uniquely determined by analytical expressions. The configuration is also benefited with closed-form expression to calculate the number of DOFs. Compared to the existing sparse array designs, the proposed configuration achieves more DOFs and wider array aperture for a given number of sensors. Moreover, the Pdis-ULAs structure desirably produces a hole-free resulting co-array. Owing to these improvements, the proposed antenna array scheme can accurately resolve the DOAs of several sources and achieves superior DOA estimation performance in under-determined conditions. Numerical works are carried out to validate the effectiveness of the Pdis-ULAs configuration. [ABSTRACT FROM AUTHOR]

Due to the constraint of spectrum availability in the recent era, technologies such as cognitive radio and spectrum sensing have found a central stage in the communications arena. Automatic modulation classification (AMC) plays a pivotal role in most of these technologies. AMC for Multiple-Input Multiple-Output (MIMO) systems is a domain that still lacks the due attention. Keeping in view the recent advancements in the field of artificial intelligence, we propose two relatively simple neural network architectures, i.e., Sparse Autoencoders(SAE) based Deep Neural Network (DNN) and Radial Basis Function Network (RBFN) for AMC of Space-Time-Block-Codes(STBC)-MIMO systems. An assorted set of features is proposed on the basis of distribution analysis to train these classifiers. Limited-memory Broyden–Fletcher–Goldfarb–Shanno(L-BFGS) algorithm and the least square method is used for weight optimization of DNN and RBFN, respectively. The impact of channel estimation error on the classification outcome is thoroughly investigated for blind classification scenarios. Performance comparison of the proposed methods with one of the most recent works in this context validates the effectiveness of proposed features and classifiers. Moreover, comparison with optimal Maximum-Likelihood(ML) based classifier and state of the art machine learning algorithms including, Adaptive Boosting (AdaBoost) and Convolutional Neural Networks (CNN) is also carried out. Simulation results substantiate the viability of proposed architectures for three different configurations of the STBC-MIMO system for perfect channel state information (CSI) and blind scenarios amidst channel estimation error. [ABSTRACT FROM AUTHOR]