The non‐orthogonal multiple access (NOMA) approach enables a number of users to share the same resource via superposition coding in the transmitter and successive detection in the receiver. In this study a power allocation (PA) approach based on the proportional fair division technique is proposed. In this regard, power is assigned to users such that it ensures the fairness of NOMA follows that of orthogonal multiple access. A straight forward approach that achieves this objective is stated and is followed by proposing three different algorithms. These algorithms loosen the strict proportionality criterion to fulfil the data rate of a specific user. Also, a new fairness index for NOMA based on data rate ratios is defined. Afterwards, a low‐complexity strategy based on water filling (WF) for PA amongst resources is proposed. This second PA stage aims at improving the data rate of users. The proposed approaches are applied to NOMA systems with different pairing strategies and results are compared. Results show that the proposed approaches improve the fairness of NOMA and WF increases the total system rate.

We consider downlink of a multiuser massive multiple-input multiple-output (MIMO) system and focus on reducing the hardware costs by using a single common power amplifier and separate phase shifters (PSs) for antenna front-ends. In the previous literature, the use of analog PSs in this setup has been considered. Here, we study the use of practical digital PSs, which only support a limited set of discrete phases. Considering the sum of interference powers as a metric, we formulate the corresponding nonlinear discrete optimization problem and solve for the phases to be used during transmission. We devise a low-complexity algorithm, which employs a trellis structure providing suboptimal, but efficient and effective solutions. We demonstrate via examples that the proposed solutions have comparable performance to conventional analog PS-based algorithms. Furthermore, we prove that by utilizing discrete-phase constant envelope precoding, the interference can be made arbitrarily small by increasing the number of antennas. Therefore, the asymptotic gains promised by massive MIMO systems are preserved. We also obtain closed-form expressions for the rate loss due to errors in the phase and amplitude of the PSs, for both low and high SNR regimes.

The authors study cooperative security in the physical layer of wireless systems based on the recently developed polar codes for multiple access channel (MAC). Specifically, the authors first consider the case of a m ‐user MAC with external eavesdropper. Using polar alignment, the authors formulate a discrete optimisation problem where security and reliability criteria can be handled separately over the bases of a set of deterministic binary matrices. A discrete algorithm with incrementally polynomial complexity is used to maximise the uniform sum secrecy rate of users. Moreover, the proposed coding scheme is shown to achieve strong security for any subset of users. The authors next examine the case of minimum number of cooperative helpers to fulfil a feasible secrecy rate requirement at the legitimate user. Here, a low‐complexity suboptimal algorithm is presented with at most one helper more than the optimal solution. Using Tal–Sharov–Vardy implementation of MAC polar codes, secure polar coding is implemented for a 2‐user Gaussian wiretap MAC channel. The upper and lower bound of block error probability are compared, respectively, at the legitimate receiver and the eavesdropper. The results demonstrate clearly that with sufficiently long block length, strong secrecy with respect to the eavesdropper is achieved, while block error probability approaches 0.5.

Personal style is the cause of interpersonal variations, which play an important role in facial expression recognition. In this study, a model has been proposed to generate diverse sequences of virtual samples for a new subject. These sequences are thought to enrich the training set in order to increase robustness of recognition with respect to individual variations and improve generalisation to the new person. In the manifold‐based parametric motion model, the trajectory of the source person has been used to estimate and conduct the virtual facial expression vectors of the target person. In the recognition experiments, images are represented in the lower‐dimensional feature space, whereas the virtual vectors are generated in the feature space. The accuracy of the independent system shows the effectiveness of samples in improving the performance of the system based on the limited data of the new person. The accuracy of seven expressions is 90.65%, which is an improvement over the baseline model, which is 86.11%, and represents a significant ( P < 0.05) improvement over the baseline method, which is 83.4%.

A precoding scheme for physical layer security of multiple‐input single‐output (MISO) wiretap channel with spatial correlation is designed. Quality‐of‐service (QoS) of the link is defined in terms of upper bounds on average symbol error rate function at Bob (legitimate user) and Eve (illegitimate user). Specifically, two problems are considered. First, a precoder matrix is designed to minimise the average transmitted power subject to QoS requirements at Bob and Eve. Next, we propose two algorithms to minimize QoS of illegitimate party for a given reliability level, depending on whether main user link has no correlation or is fully correlated. Our result for uncorrelated case demonstrate that by increasing the allocated power, main user can increase secrecy level up to an optimum point above which both legitimate and illegitimate receivers experience adequate QoS in their links. In fully correlated case, the problem is identified as an instance of concave minimisation over a polytope, and optimum power allocation is obtained via the widely known vertex enumeration algorithm. In both cases, our simulations validate the analysis significantly. The results confirm that linear precoding is able to trade average power against minimum achievable Eve performance.

The effect of large‐scale fading variations over massive multiple input multiple output (MIMO) antenna array on sum‐capacity of massive MIMO system has not been thoroughly investigated in the literature. This study considers a multiuser massive MIMO system with a Rayleigh fading channel that takes into account large‐scale fading variations over base station antenna array. Two scenarios are investigated: distributed antenna base station and linear array base station. In both scenarios, the authors obtain an approximate closed‐form expressions for uplink ergodic sum‐capacity for both low and high signal‐to‐noise ratio (SNR) regimes. It is shown that the proposed closed‐form expressions are accurate in a wide range of practical SNRs; for example, the approximation error is below 10% for SNRs lower than −10 dB and higher than 17 dB for low‐SNR and high‐SNR closed‐form expressions, respectively. It is also shown that the proposed closed‐form expressions are not only valid for massive MIMO scenario but also for a system with a few number of base station antennas. The numerical results show that the proposed closed‐form expressions have much less computational complexity than previous works.

This study examines the performance of person‐independent facial expression recognition improved by adapting the system to a given person. The proposed method transfers the style of particular subjects to the semi‐style‐free space. There is no need to change the person‐independent classifier in order to improve the performance. The style transfer mapping (STM) has been proposed in image‐based classification. The challenges of employing this technique in video‐based facial expression recognition are: estimating STM from image sequences of each subject (adaptation data) and projecting new sequential data of each subject in semi‐style‐free space. A mixture of ‘binary support vector machines’ and ‘hidden Markov models’ were employed to overcome these challenges. Moreover, virtual samples generated by using the person's neutral samples were used to estimate STM. Experimental results on the CK+ database confirm the efficiency of the proposed method in recognition rate improvement.

The authors consider the resource allocation issue in multiple‐input multiple‐output‐orthogonal frequency division multiplexing‐based cooperative cognitive radio networks with the decode‐and‐forward (DF) as the cooperation strategy. The dual decomposition technique is recruited to obtain an optimal subcarrier pairing, relay selection and power allocation. The optimal resource allocation is performed subject to the individual power constraints in source and relays so that the sum‐rate is maximised while the interference induced to the primary system is kept below a pre‐specified interference temperature limit. Moreover, because of the high computational complexity of the optimal approach, a sub‐optimal algorithm is further proposed. In the sub‐optimal scheme, the joint allocation of the resources is performed taking into account the channel qualities, the DF cooperation strategy, the interference induced to the primary system and the individual power budgets. The performance of different approaches and the impact of the constraint values and deploying multiple‐antennas at users are explored through numerical simulations.

We consider a MIMO-OFDM-based cooperative cognitive radio network (CCRN) in which there exists a number of regenerative relays to cooperate with the cognitive base station (CBS) in serving an SU. Our objective is to optimize the transmit covariance matrices at the CBS and the relays and obtain the optimal subcarrier pairing, relay assignment, where the dual-decomposition technique is recruited as a tool. The optimal resource allocation is performed subject to the individual power constraints in the CBS and relays and the interference power constraint on the primary system. Moreover, due to the high computational complexity of the optimal approach, a suboptimal algorithm is further proposed. The joint allocation of the resources in the proposed suboptimal algorithm is performed taking into account the decode-and-forward cooperation strategy, the interference imposed on the primary network, and the power budgets at the CBS and the relays. The performance of different approaches and the effect of deploying multiple antennas at users are explored through simulations.

Maximisation of the sum‐rate of secondary users (SUs), equipped with multi‐antenna transmitters and receivers, is considered in the context of multi‐input–multi‐output antenna multi‐band cognitive radio networks (MIMO‐MB‐CRNs) with coexisting primary users (PUs). The total interference power introduced to the PUs is constrained to maintain reliable communication for them. An interference channel configuration is considered for ad hoc networking, where the receivers treat the interference from undesired transmitters as noise. Using game theory approach, the strong duality in convex optimisation and the primal decomposition method, a low complexity semi‐distributed algorithm is proposed for spectrum sharing and power allocation for MIMO‐MB‐CRNs. The key idea behind the algorithm is the introduction of a diagonal block pricing factor matrix for each SU link. This matrix regulates network interference by encouraging SU links to work in a more altruistic manner. The proposed algorithm is configured in two iterative algorithms, Jacobi and Gauss–Seidel algorithms, and their performance is investigated through simulations. The simulation results showed that the proposed algorithm dramatically improves sum‐rate and achieves higher energy efficiency, compared with other algorithms.

In this study, the problem of resource allocation in multiple‐input multiple‐output–orthogonal frequency division multiplexing‐based cooperative cognitive radio networks is considered. The cooperation strategies between the secondary users is the decode‐and‐forward (DF) strategies. In order to obtain an optimal subcarrier pairing, relay assignment and power allocation in the system, the dual decomposition technique is recruited. The optimal resource allocation is realised under the individual power constraints in source and relays, so that the sum rate is maximised, whereas the interference induced to the primary system is kept below a pre‐specified interference temperature limit. Moreover, because of the high computational complexity of the optimal approach, a suboptimal algorithm is further proposed. The joint allocation of the resources in suboptimal algorithm is carried out taking into account the channel qualities, the DF cooperation strategy, the interference induced to the primary system and the individual power budgets. The performance of the different approaches and the impact of the constraint values and deploying multiple antennas at users are discussed through the numerical simulation results.

We study the problem of transmission of binary input non-linear functions over a network of mobiles based on CDMA. Motivation for this study comes from the application of using cheap measurement devices installed on personal cellphones to monitor environmental parameters such as air pollution, temperature and noise level. Our model resembles the MAC model of Nazer and Gastpar except that the encoders are restricted to be CDMA encoders. Unlike the work of Nazer and Gastpar whose main attention is transmission of linear functions, we deal with non-linear functions with binary inputs. A main contribution of this paper is a lower bound on the computational capacity for this problem. While in the traditional CDMA system the signature matrix of the CDMA system preferably has independent rows, here the signature matrix of the CDMA system is viewed as the parity check matrix of a linear code, reflecting our treatment of the interference. We also introduce the problem of Slepian-Wolf compression with the same compression matrix.

In the cognitive radio (CR) networks consisting of selfish users competing for spectrum resources, the social optimum is usually not achieved at the Nash equilibrium (NE) of the power control game, since selfish users are only interested in their own benefit. In this study with the aim of improving the NE efficiency, the authors extend the pricing concept to a multi-channel multiple-in multiple-out (MIMO) CR scenario and propose two iterative algorithms for power control and channel allocation in such systems. Specially, the authors consider both linear and non-linear pricing methods and derive the optimal pricing factor for both scenarios and prove the existence and uniqueness of the NE. Simulation results prove the outstanding performance of the proposed MIMO cognitive system considering price-based power control over the non-price-based MIMO cognitive systems.

This paper aims to provide a restoration algorithm for the Pahlavi or middle-age Persian manuscript. This is the preliminary document processing view to this area. The central idea is based on the morphological analysis and connected component concept. The proposed algorithm uses the mathematical morphology and connected component concept to segment the line, word, and character overlapped Pahlavi documents and prepares those texts for OCR application. To evaluate the performance of the algorithm, it has been tested on 200 pages of the Pahlavi documents. The algorithm has a good success on document restoration and segmentation. Numerical results indicate that the proposed algorithm can remove the noise and destructive effects. The results also show 99.14% accuracy on the baseline detection, 97.35% accuracy on the text line extraction and removing other lines overlaps, and 99.5% accuracy for segmenting the extracted text lines to their components.

Pseudo-Zernike polynomials are well known and widely used in the analysis of optical systems. In this paper, a weighted Pseudo-Zernike feature is introduced for face recognition. We define a weight function based on the face local entropy. By this weight function, the role of high information region, i.e. eyes, noses and lips, will be intensified on the extracted features. For classification, a single hidden layer feedforward neural network has been trained. To evaluate the performance of the proposed technique, experimental studies are carried out on the ORL database images of Cambridge University. The numerical results show 98.5% recognition rate on the ORL database with the order 8 of weighted Pseudo-Zernike feature and 44, 98, 40 neurons for the input, hidden, and output layers while this amount is 96% for the original Pseudo-Zernike.

This paper investigates a novel method to derive a set of binary sequences from a chaotic dynamical system. We modify the previous methods using statistical properties of chaotic sequences. It has been shown that the proposed sequences have good performance according to merit factor and W-index criteria and can be used as a spreading sequence in asynchronous DS-CDMA systems.