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This paper proposes two algorithms for hybrid (Analog–Digital) beamforming in a single-user millimeter-wave (mm-wave) multi-input multi-output (MIMO) systems under frequency selective channels. Hybrid architecture has a potential to reduce the number of radio frequency (RF) chains to far less than the number of antennas and, it results in low hardware complexity, power efficiency and cost-saving to the system. Since practical broadband systems are frequency selective in nature therefore, the challenging aspect of this problem is to have only one analog RF processing matrix at source and destination over the entire frequency band. To address this problem for spectral efficiency maximization, the first algorithm performs multi-linear singular value decomposition on different sub-carriers to derive the common analog combiner over the allocated frequency-spectrum. Then, a problem is formulated for designing the common analog precoder that attempts to extract the optimal phase values for gain maximization of the equivalent channel observed from baseband processing units at transmitter and receiver. To significantly reduce the computational complexity in comparison to the first algorithm, the second algorithm employs classification of beamforming vectors for gain maximization of the equivalent baseband channel over all sub-carriers to find the analog RF precoding/combining matrices. Digital baseband processing components are derived by diagonalizing the equivalent baseband channel corresponding to each frequency-carrier. Computational complexity of the second algorithm is significantly less than the several existing designs. Computer simulations reveal that the proposed algorithms show near-optimal performance under diverse scenarios of system configuration parameters. [ABSTRACT FROM AUTHOR]

Quantum computing is a field of study aimed at developing technologies based on the principles of quantum theory. In this research area, enormous theoretical progress has been made, but at the current state, few quantum algorithms have been developed. It is very hard to efficiently construct new ones. The complexity is due to the non-intuitive nature of quantum operations. To overcome this obstacle, we opt for the integration of an automatic design approach. In this paper, we propose an adapted version of BackTracking algorithm allowing complete but optimal exploration of the quantum circuits space. For a given problem, the test of possible quantum gate sequences is optimized by using a constraint making it possible to ignore all unnecessary calculation in an efficient manner. In addition, solutions are generated automatically without resorting to mathematical formulas. Our approach allowed us to generate two new versions of controlled quantum teleportation. In the first version, the controller can switch the teleported Qubit between two possible distant receivers, while in the second version, this controller can choose between two different transmitters. [ABSTRACT FROM AUTHOR]

In this paper, a reversible data hiding algorithm for audio files based on code division multiplexing (CDM) is proposed. In the scheme, the orthogonal spreading sequences are employed to carry the embedding data, and the host audio file can also be recovered completely after the secret message has been extracted accurately. At the same time, according the orthogonal character of the spreading sequences, the secret message can be embedded into the audio files repeatedly, and most elements of the spreading sequences are mutually canceled in the process of multi-level data embedding, which maintains the audio file in good auditory even at high data embedding capacity. Moreover, only the receiver who holds the same spreading sequences, as the sender can restore the embedded data, which enhance the security of the proposed scheme. As shown in the experimental results, the CDM based reversible data hiding (RDH) algorithm for audio files can achieve higher data embedding capacity at the same audio distortion compared with those state-of-the-art audio RDH algorithms. [ABSTRACT FROM AUTHOR]

Media-based modulation (MBM) is a novel modulation technique that can improve the spectral efficiency of the existing wireless systems. In MBM, multiple radio frequency (RF) mirrors are placed near the transmit antenna(s) and are switched ON/OFF to create different channel fade realizations. In such systems, additional information is conveyed through the ON/OFF status of RF mirrors along with conventional modulation symbols. A challenging task at the receiver is to detect the transmitted information symbols and extract the additional information from the channel fade realization used for transmission. In this paper, we consider a massive MIMO (mMIMO) system where each user relies on MBM for transmitting information to the base station, and investigate the problem of symbol detection at the base station. First, we propose a mirror activation pattern (MAP) selection based modified iterative sequential detection algorithm. With the proposed algorithm, the most favorable MAP is selected, followed by the detection of symbol corresponding to the selected MAP. Each solution is subjected to the reliability check before getting the update. Next, we introduce a K favorable MAP search based iterative interference cancellation (KMAP-IIC) algorithm. In particular, a selection rule is introduced in KMAP-IIC for deciding the set of favorable MAPs over which iterative interference cancellation is performed, followed by a greedy update scheme for detecting the MBM symbols corresponding to each user. Simulation results show that the proposed detection algorithms exhibit superior performance-complexity trade-off over the existing detection techniques in MBM-mMIMO systems. [ABSTRACT FROM AUTHOR]

In this paper, the main research object is evolution algorithm applied for an ultra-wideband three-dimensional (3D) circular antenna array and the significance of elevation angles and their influence on the system performance are highlighted. The 3D channel is calculated by means of 3D shooting and bouncing ray/image techniques which specify multipath elevation angles and azimuth for horizontal plane angles. The capacities of the two-dimensional (2D) and three-dimensional transmitting antenna arrays have been presented. Beam-synthesizing techniques are applied at the transmitter to focus the transmitter energy for the sake of mitigating the multi-path effect and improving channel capacity. A combination of asynchronous particle swarm optimization (APSO) and dynamic differential evolution (DDE) methods are introduced to make adjustment to the length of the feed line on each array element for the maximum capacity. In comparison with 2D azimuth-only antenna arrays, a higher directive gain can be achieved from the 3D antenna arrays results in high channel capacity. Besides, it is discovered that the capacity for the 3D array improves by as much as over 10% when compared to that for the 2D array. As revealed by numerical results, APSO is capable of obtaining better beam-forming pattern to improve the channel capacity than DDE by about 9%. Not only does our research provide qualitative outcomes, it also presents quantitative results. [ABSTRACT FROM AUTHOR]

This paper considers a passive target localization problem based on the noisy time of arrival measurements obtained from multiple receivers and a single transmitter. The maximum likelihood (ML) estimator for this localization problem is formulated as a highly nonlinear and non-convex optimization problem, where conventional optimization methods are not suitable for solving such a problem. Consequently, this paper proposes an improved adaptive hybrid firefly differential evolution (AHFADE) algorithm, based on hybridization of firefly algorithm (FA) and differential evolution (DE) algorithm to estimate the unknown position of the target. The proposed AHFADE algorithm dynamically adjusts the control parameters, thus maintaining high population diversity during the evolution process. This paper aims to improve the accuracy of the global optimal solution by incorporating evolutionary operators of the DE in different searching stages of the FA. In this regard, an adaptive parameter is employed to select an appropriate mutation operator for achieving a proper balance between global exploration and local exploitation. In order to efficiently solve the ML estimation problem, this paper proposes the well-known semidefinite programming (SDP) method to convert the non-convex problem into a convex one. The simulation results obtained from the proposed AHFADE algorithm and well-known algorithms, such as SDP, DE and FA, are compared against Cramér–Rao lower bound (CRLB). The statistical analysis has been performed to compare the performance of the proposed AHFADE algorithm with several well-known algorithms on CEC2014 benchmark problems. The obtained simulation results show that the proposed AHFADE algorithm is more robust in high-noise environments compared to existing algorithms. [ABSTRACT FROM AUTHOR]

The orthogonal frequency division multiplexing (OFDM) is the most encouraging multi-carrier modulation system chosen for the high data rates but the objective is to resolve intrinsic common issue of peak to average power ratio (PAPR). The projected algorithm is illustrated in this research study which is established upon selected mapping (SLM) with pseudo-random sequence under time domain μ law companding of signal. Besides the significant competitive characteristics of conventional SLM algorithm (ConvenSLM-Algo) (Mestdagh et al. in Electron Lett 32(22):2056–2057, 1996. 10.1049/el:19961384), it undergoes the tedious complexity in generation of phase sequence and for the recovery of sequence, side information is mandatory. The key concern, thus, to eliminate the tedious problem of designing of phase sequence along with the aim of reducing the fluctuation of signal with high PAPR. Henceforth, in the projected algorithm (Projected-Algo) a noteworthy strategy has been investigated and followed for the designing of phase sequence which is very easy and for the recovery of information at receiver, side information of index of column of phase sequences can be used because of straightforwardness in its establishment. Hence, we demonstrate the effective overall excellent performance of Projected-Algo along with analysis and also comparative study of Projected-Algo outperforms the conventional OFDM system (unchanged), ConvenSLM-Algo [16], SLM with new pseudo random phase sequences (ModSLM-Algo) given in literature (Ali et al. in Canadian conference on electrical and computer engineering, 2018. 10.1109/CCECE.2018.8447835). [ABSTRACT FROM AUTHOR]

In a cellular network (CN), cellular users (CUs) located nearby machine type communications (MTC) devices (MTC-Ds) may act as uplink gateways to relay data to the base station (BS). We consider non-orthogonal multiple access (NOMA) and successive interference cancellation (SIC) at the receiver to increase the number of connected devices and the spectrum efficiency. Both underlay and overlay spectrum access modes (SAMs) are considered. We introduce a dynamic user grouping (UG) concept as a practical constraint for SIC, in order to decrease the receiver complexity. Moreover, SIC constraints are introduced based on a minimum signal-to-noise-plus-interference ratio (SINR) at the receiver. We formulate a joint dynamic UG, power allocation, and resource block (RB) assignment problem, aiming at maximizing the total sum-rate of both CUs and MTC-Ds. We transform the obtained non-convex mixed-integer programming problem into a convex problem by using a quadratic fractional programming (FP). A heuristic method is also proposed to reduce complexity. Simulation results demonstrate that the proposed solution outperforms the conventional CN (C-CN) method and the results of the proposed optimization methods are close to optimal solution obtained by the exhaustive search (ES) algorithm in terms of total average sum-rate and network connectivity, while requiring less transmit power. The heuristic method decrease the computational complexity of the FP method at the expense of a small reduction in spectrum efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we consider an energy harvesting device-to-device (D2D) communication system, where D2D transmitter can use mode A to directly communicate with D2D receiver or use mode B as a relay to assist cellular communication while communicating with D2D receiver by adopting non-orthogonal multiple access technology. Firstly, the outage probability expression in two modes is derived, and the communication mode is determined according to outage performance. Then, assuming that the full system information is available, the channel allocation and relay selection are completed by Kuhn–Munkres algorithm, and the offline power allocation of D2D users is realized by reinforcement learning. Next, the offline optimization results are taken as the training data set to train the neural network, and the optimal model of the transmission power is obtained. Considering the transmission power constraint, the online power allocation optimization algorithm is further proposed. Numerical results demonstrate the accuracy of derived outage probability, and the proposed resource allocation algorithm can improve the performance of hybrid system. [ABSTRACT FROM AUTHOR]

To balance the output stability and maximum efficiency of a system, an efficiency optimization method based on adaptive frequency control is proposed. In this paper, load transmission is carried out using a DC–DC converter at the receiving end. When the load changes, controlling the rectified output voltage is carried out to realize the maximum efficiency point tracking. Meanwhile, the duty cycle of the rear stage DC–DC converter is changed to keep the output voltage constant. The sampled rectified voltage is compared with the estimated value and the resulting error data are sent to the system transmitter through ASK modulation wireless communication. Then the transmitter demodulation communication information through PID algorithm control is used to achieve the frequency of the adaptive adjustment. The feasibility of the proposed method has been verified by the simulation and experimental results. When the output voltage is 5 V, the constant voltage accuracy is within ± 1%, the maximum efficiency is up to 79.2%, and the dynamic response time is only 160 ms. [ABSTRACT FROM AUTHOR]

Rendezvous control of multiple robots without losing network connectivity has important implications in multi-robot system including formation control, coordinated task assignments, and cooperative robotic missions. This paper introduces a new coordinate-free, bearing-based algorithm to enable rendezvous of distributed mobile robots at any designated leader robot node using hierarchical tracking of wireless network topology. An assumption is made that the robot can only sense and communicate with their neighbors (i.e., local sensing). The proposed approach preserves connectivity during the rendezvous task, adapts to dynamic changes in the network topology (e.g., losing or re-gaining a communication link), and is tolerant of mobility faults in the robots. We theoretically analyze the proposed algorithm and experimentally demonstrate the approach through simulations and extensive field experiments. The results indicate that the method is effective in a variety of realistic scenarios in which the robots are distributed in a cluttered environment. [ABSTRACT FROM AUTHOR]

This paper proposes a novel efficient precoding algorithm to maximize the rate of the cognitive link, where a pair of multiple-input multiple-output cognitive radio users shares the spectrum allocated to multiple primary users as long as the interference power is acceptable. In our method, the precoding vectors are firstly obtained by solving an unconstrained convex problem which is formulated by using the penalty function idea and has a closed-form solution. Then, power is allocated to different precoding vectors to satisfy both the transmit-power constraint and interference-power constraints through interior method. Moreover, an effective set of the penalty weights is presented. Our method has much lower complexity than the optimal solution and similar complexity to other low-complexity methods. Simulation results show that our method significantly outperforms the existing low-complexity methods and has almost the same performance as the optimal solution. [ABSTRACT FROM AUTHOR]

In this paper, two new one-bit feedback beamforming algorithms are proposed to achieve carrier phase alignment at the receiver for distributed transmit beamforming. We term two algorithms as continuous-negative one-bit feedback algorithm (CN) and directional-negative one-bit feedback algorithm (DN), respectively. They both are based on a new mechanism, referred to as the stage-threshold mechanism, in which there is different threshold value for different stage to determine whether transmitters step into the next stage and transmitters adopt the corresponding perturbation size in certain stage. During the initial stages, the perturbation size of the proposed algorithms is larger to speed up the convergence of synchronization, while the value of perturbation size decreases gradually as the order of stage increasing to keep the stability of convergence. CN algorithm directly controls the perturbation size, but DN algorithm consists of two steps, first to determine the direction of the perturbation size and then to adjust its amplitude. In comparison with existing one-bit feedback beamforming algorithms, the proposed algorithms provide their superiority while the number of transmitters is small. The given simulation results illustrate the main characteristics of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance. [ABSTRACT FROM AUTHOR]

An algorithm for reconstructing images of reflectors from echo signals that propagate in a test object, which consists of several regions with different acoustic properties, is considered. The ray trajectories are calculated using the method of direct construction of the family of rays that escape from the point where a transmitter is located but not the Fermat variational principle. After the family of rays is constructed, their belonging to a certain acoustic scheme can be analyzed and the approximation of the calculated delays on the spatial mesh of the image reconstruction region (IRR) can be performed. This will allow the reconstruction of both the pulse travel time from the transmitter to any point in the IRR and back to the receiver and the attenuation of the pulse amplitude caused by the divergence, reflection, and refraction effects at the boundaries of the regions that constitute the test object. Numerical and model experiments show the working capacity of the proposed algorithm for reconstructing reflector images. [ABSTRACT FROM AUTHOR]