Polar codes are one of the most powerful types of forward error correction codes. These codes are now adopted in the 5G standard for control channels and are the primary contender for future communication systems. In this paper, a new data transmission system is proposed using adaptive rate non-systematic polar code and adaptive Hierarchical Quadrature Amplitude Modulation (HQAM) to improve the error performance of the system according to the channel quality over Gaussian and Rician channels. To determine the high and low priority bits for HQAM, a new algorithm is proposed in case of non-systematic polar code where the information bits are inherited in the codeword. In the proposed system, both polar code rate and HQAM parameter constellation distances are adaptive according to the channel quality and target block error rate to enhance the spectral efficiency. Since HQAM does not change the modulation order, then the proposed system offers same demodulator complexity in contrast to traditional adaptive modulation with various modulation orders. Simulation results prove that the proposed system achieves the target block error rate at lower bit energy to noise power spectral density ratio, in addition to better spectral efficiency compared to adaptive rate polar code with traditional QAM system. Moreover, the proposed system achieves superior spectral efficiency than fixed coding and modulation system and traditional adaptive modulation and coding system.

Massive MIMO systems were utilized in overlay Cognitive Radio (CR) networks to allow simultaneous primary and secondary data transmission while enhancing the spectral efficiency. However, the precoder design of a massive MIMO system especially in the overlay CR paradigm usually has a trade-off between achieved data rate and complexity. In this paper, the precoder design for overlay Cognitive Radio (CR) massive MIMO system is introduced, where a two-stage precoder that accommodates Transmit Antenna Selection (TAS) is proposed for the Secondary Base Station (SBS). The unselected antennas in the cognitive base station are proposed to be utilized to relay the data of the Primary Users (PUs) to maximize the network sum rate. The proposed precoder design for primary data aims to cancel the interference inflicted on Secondary Users (SUs) as a result of relaying the primary data. Moreover, a fast algorithm is proposed which aims to select and distribute the SBS antennas for primary and secondary data transmission to achieve better data and convergence rates, this algorithm is called Transmit Antenna Selection and Distribution (TASD). Simulation results show that the proposed precoders' design and the TASD algorithm enhance the total system sum rate (primary and secondary rates) compared to the conventional TAS (where the unselected antennas were not used to relay PUs' data). This enhancement was achieved by relaying primary data without affecting the rate of SUs. As a result, the computational time of the TASD algorithm is reduced by 52% compared to the full array case while the total sum rate of the algorithm is only 3% less than the full array scenario. Furthermore, the results in case of using a practical correlated channel proved the robustness of the proposed TASD algorithm, as it achieved nearly the same results compared to uncorrelated channels.

Polar code is a recent forward error correction technique that is characterized by its low encoding/decoding complexity and good error performance. In this paper, a complete image transmission system (transmitter and receiver) is proposed to improve the image quality over different types of channels such as Gaussian, Rayleigh and Rician channels. The proposed system is based on encoding the most significant quantized Discrete Cosine Transform (DCT) coefficients of the digital image using adaptive rate polar coding, by changing the number of frozen bits depending on the number of significant DCT coefficients that depend on the channel quality. Simulation results reveal that the proposed system achieves better performance compared to the coded digital transmission schemes in terms of the Structural SIMilarity (SSIM) index and the Peak Signal to Noise Ratio (PSNR) for different sizes of images. Moreover, it is not subject to “cliff effect” and exhibits improvement in image quality according to the channel quality.

The huge bandwidth and immunity to electromagnetic interference make visible light communication (VLC) systems the preferred technique for many applications. Unfortunately, the superposition of multiple subcarriers in VLC orthogonal frequency division multiplexing systems leads to a high peak-to-average power ratio (PAPR). So, in this study, we aim to reduce PAPR in VLC systems and improve the system performance by proposing non-distorting PAPR reduction techniques like precoding techniques as it doesn’t affect the system data rate because they do not require any obligatory transmission of side information. Moreover, it has a very good ability to reduce the PAPR without affecting the system BER performance. So, different precoding reduction techniques are proposed like discrete cosine transform (DCT), discrete sine transform (DST), discrete Hatley transform (DHT), and Vandermonde like matrix (VLM), to address the high PAPR and light-emitting diode-restricted linear range problems in VLC systems. The proposed technique using DHT, DCT, DST, and VLM provided a significant advantage in reducing the PAPR by 1.35 dB, 1.46 dB, 2.12 dB, and 2.17 dB, respectively. So the proposed technique is based on using the VLM precoding technique to achieve maximum reachable PAPR reduction value. Also, a comparison of the presented work and related literature reviews for PAPR reduction techniques are held to ensure the validity and effectiveness of the proposed scheme.

Human-object interaction (HOI) detection is the task of predicting the visual relationships between humans and their surroundings in images and videos by locating and inferring the interactions between human-object pairs. The majority of existing models have approached this task by detecting human and object instances and predicting interactions between them using a single model and relying on visual features to differentiate between different actions. In this article, we propose a novel method for solving the HOI detection problem by employing ensemble voting on simple models that use only spatial features to predict human-object pair actions. Additionally, we solve the false-positive pairs generated by mis-grouping and non-interaction objects in the image using a bipartite matching. Our proposed approach outperforms many state-of-the-art models on the V-COCO dataset while requiring less inference time.

Visible light communications (VLC) are gaining an important role in 6G network deployment scenarios. Although 6G networks are planned to deliver incredibly high throughput and fulfill new applications, present frequency bands may be insufficient. Furthermore, 6G will provide improved coverage by merging terrestrial networks with underwater, air, and space networks. So VLC is used instead of the standard wireless communications which is incapable of providing such high-data rates for the non-terrestrial networks. VLC is a power-efficient and safe wireless communication system that operates in the visible light spectrum. In addition, VLC overcomes RF communication bandwidth limitations. In this paper, the overall aggregated throughput, data rate, power, and spectrum-efficiency in VLC systems will be improved by promoting a novel unipolar system titled improved aggregated rate for optical orthogonal frequency division multiplexing (IARO-OFDM). Moreover, introducing the precoding peak to average power ratio (PAPR) reduction technique to get a power efficient system and enhance the VLC system performance. Also, the authors provide a mathematical description and evaluation for the proposed IARO-OFDM system, in addition to comparing the proposed one with other current approaches which demonstrate that IARO-OFDM has a high data rate ratio (43.75%) with an acceptable system bit error rate system performance compared to other existing schemes.

Human-object interaction (HOI) detection is the detection of a human's relationship with an object in still images and videos. The majority of HOI detection methods rely on appearance features as the primary feature for detecting the relationship between humans and objects. Furthermore, the model's performance is affected by the abundance of false-positive pairs generated by the image's non-interactive human-object pairs and human-object mis-grouping. In this paper, we propose "Spatial-Net", a new HOI detection approach in still images. In the proposed approach, the HOI problem is divided into two main tasks, namely pair-prediction and global-rejection. In the pair-prediction task, the spatial relationship is adopted to predict the human-object interaction for each human-object pair using spatial features that contains spatial map which is a single channel image that represents human-object pairs including body parts and object masks, relative geometry features such as relative size, relative distance, and intersection-over-union between body part and objects, and weighted distance that is used as body part attention deterministic model. In the global-rejection task, an augmented model is employed to reject false positive pairs. We use the Hungarian matching technique to assign human-object pairs for each action and human-centric model to reject the non-interaction human-object pairs according to semantic co-occurrence between human and object. The experimental results on the V-COCO dataset demonstrate that the proposed Spatial-Net outperforms many state-of-the-art HOI models with less inference time.

The dense deployment of small cells (SCs) in the 5G heterogeneous networks (HetNets) fulfills the demand for vast connectivity and larger data rates. Unfortunately, the power efficiency (PE) of the network is reduced because of the elevated power consumption of the densely deployed SCs and the interference that arise between them. An approach to ameliorate the PE is proposed by switching off the redundant SCs using machine learning (ML) techniques while sustaining the quality of service (QoS) for each user. In this paper, a linearly increasing inertia weight–binary particle swarm optimization (IW-BPSO) algorithm for SC on/off switching is proposed to minimize the power consumption of the network. Moreover, a soft frequency reuse (SFR) algorithm is proposed using classification trees (CTs) to alleviate the interference and elevate the system throughput. The results show that the proposed algorithms outperform the other conventional algorithms, as they reduce the power consumption of the network and the interference among the SCs, ameliorating the total throughput and the PE of the system.

Visible Light Communications (VLC) are receiving increased attention in the wireless communications research community. VLC is secured, power efficient, and operates in the visible light range, thus RF communication bandwidth limitation is overcome. In this article, the authors enhance the data rate, system complexity, power efficiency, and spectrum efficiency in VLC systems. An innovative unipolar transceiver system is proposed, mathematically analyzed, and compared with other existing techniques and it demonstrates to have a very high data rate ratio (43.75%) with a good system bit energy to noise ratio ${(E}_{b}/N_{O})$ compared to other existing techniques. Development for the traditional asymmetrically and symmetrically clipping optical (ASCO-OFDM) system is also proposed, which involves combining a modified receiver with the ASCO-OFDM system traditional transmitter. The proposed receiver reduces the system complexity by O ( $N\log _{2}N$ ) with better $E_{b}/N_{O}$ than the conventional ASCO-OFDM. Detailed analysis, simulation results, and comparison of the proposed systems with the existing systems are presented beside a brief assessment of existing techniques.

Recently, generalized polar codes were introduced to provide more code lengths and rates without the need for shortening or puncturing. However, as the size of the kernel matrix increases, computing the Log-Likelihood Ratio (LLR) functions in successive cancellation decoder for these codes becomes mathematically more complicated. In this paper, a new simplified general method is proposed to calculate these LLR functions based on the schematic diagram of the selected kernel matrix for sizes higher than 2. Our proposed method fragments the main block into some basic components whose formulas have been previously proven by Arikan for $2 \times 2$ kernel matrix. The validity of the resulting LLR functions is tested on different kernel matrices and proven to be similar to those in literature.

Polar codes are featured by their low encoding/decoding complexity for symmetric binary input-discrete memoryless channels. Recently, flexible generic Successive Cancellation List (SCL) decoders for polar codes were proposed to provide different throughput, latency, and decoding performances. In this paper, we propose to use polar codes with flexible fast-adaptive SCL decoders in Digital Video Broadcasting (DVB) systems to meet the growing demand for more bitrates. In addition, they can provide more interactive services with less latency and more throughput. First, we start with the construction of polar codes and propose a new mathematical relation to get the optimized design point for the polar code. We prove that our optimized design point is too close to the one that achieves minimum Bit Error Rate (BER). Then, we compare the performance of polar and Low-Density Parity Check (LDPC) codes in terms of BER, encoder/decoder latencies, and throughput. The results show that both channel coding techniques have comparable BER. However, polar codes are superior to LDPC in terms of decoding latency, and system throughput. Finally, we present the possible performance enhancement of DVB systems in terms of decoding latency and complexity when using optimized polar codes as a Forward Error Correction (FEC) technique instead of Bose Chaudhuri Hocquenghem (BCH) and LDPC codes that are currently adopted in DVB standards.

Macro cells' (MCs) densification with small cells (SCs) is one of the promising solutions to cope with the increasing demand for higher data rates in 5G heterogeneous networks (HetNets). Unfortunately, the interference that arises between these densely deployed SCs and their elevated power consumption have caused huge problems facing the 5G HetNets. In this paper, a new soft frequency reuse (SFR) scheme is proposed to minimize the interference and elevate the network throughput. The proposed scheme is based on on/off switching the SCs according to their interference contribution rate (ICR) values. It solves the interference problem of the densely deployed SCs by dividing the cell region into center and edge zones. Moreover, SCs on/off switching tackles the elevated power consumption problem and enhances the power efficiency of the 5G network. Furthermore, our paper tackles the irregular nature problem of 5G HetNets and compares between two different proposed shapes for the center zone of the SC: circular, and irregular shapes. Additionally, the optimum radius of the center zone, which maximizes the total system data rate, is obtained. The results show that the proposed scheme surpasses the traffic and the random on/off switching schemes, as it decreases the outage probability and enhances the total system data rate and power efficiency. Moreover, the results demonstrate the close performance of both the irregular and circular shapes for the center zone.

Retinal images provide a simple non-invasive method for the detection of several eye diseases. However, many factors can result in the degradation of the images’ quality, thus affecting the reliability of the performed diagnosis. Enhancement of retinal images is thus essential to increase the overall image quality. In this work, a wavelet-based retinal image enhancement algorithm is proposed that considers four different common quality issues within retinal images (1) noise removal, (2) sharpening, (3) contrast enhancement and (4) illumination enhancement. Noise removal and sharpening are performed by processing the wavelet detail subbands, such that the upper detail coefficients are eliminated, whereas bilinear mapping is used to enhance the lower detail coefficients based on their relevance. Contrast and illumination enhancement involve applying contrast limited adaptive histogram equalization (CLAHE) and the proposed luminance boosting method to the approximation subband, respectively. Four different retinal image quality measures are computed to assess the proposed algorithm and to compare its performance against four other methods from literature. The comparison showed that the introduced method resulted in the highest overall image improvement followed by spatial CLAHE for all the considered quality measures; thus, indicating the superiority of the proposed wavelet-based enhancement method.

Elliptic curve plays an important role in securing critical software applications as it is one of the most powerful and widely utilized encryption algorithms. It is used in many applications such as digital signature schemes. Elliptic curve algorithms are hard to break, however, attackers find another indirect and more efficient methods to estimate secret information behind any secured systems with the help of information leakages so that they can successfully reconstruct critical objects like private keys. These methods are called side- channel attacks. In this paper we propose a software implementation of ECDSA which can counteract cache memory side-channel attack using three techniques, namely, “Fisher Yates” algorithm, volatile memory objects, and thread locking.

Localization is a fundamental problem in wireless sensor networks. Localization means the determination of geographical locations of sensor nodes, consequently detecting the event location and to initiate a prompt action whenever necessary. The localization process passes with three phases distance and/or angle estimation phase, position phase and algorithm phase. There are many techniques can be used in each phase, some of these techniques may add additional devices, cost, power consumption, or delay to the network. This chapter includes a classification and overview of the most popular localization techniques in each phase, also high lighting the problems of these techniques and their solutions in such a way that helps in understanding localization concepts especially with respect to WSN localization.

Recently, polar codes were proposed by Arikan to achieve optimum channel capacity given by Shannon theorem with low encoding and decoding complexity. Polar code construction depends on two main foundation criteria which are kernel matrix and Bhattacharyya parameter. They are related to each other, therefore the selection method for both affects the performance of polar code. Firstly, in this study, the derivations of the bounds for Bhattacharyya parameter are proved and generalised together with a proposed method to select the best kernel matrix to achieve the optimum capacity. Then, recursive channel transformations and successive cancellation decoding of the selected 3 × 3 best kernel matrix are proved. Furthermore, a general formula for polar code complexity and hardware implementation has been discussed. Simulation results show that the achievable bit error rate for the proposed methodology of selection is the same as some existing methods with the same order of complexity, which indicates its effectiveness. Polar code performance for the selected 3 × 3 best kernel matrix is improved as the code length increases. Moreover, this proposed method is general to be for higher dimension kernel matrices.

This paper studies the precoding of a heterogeneous network composed of a massive multi-input-multi-output macro base station overlaid with several small cells. The objective of the precoding problem is maximizing the total sum rate of all users while limiting the total system power to a certain pre-defined acceptable threshold. A distributed approach is proposed for the problem and is studied for the case when the cross channels are known and when they are not. The distributed precoding is then compared against a centralized approach. Numerical results asses the performance of the two schemes in terms of the total system throughput under different conditions.

When a software implementation of a security system is considered, side channel attacks are on the spot threat. Side channel attacks, considered in this work, are a class of physical attacks in which an adversary tries to exploit physical information leakages such as timing information, power consumption, or electromagnetic radiation to estimate security system parameters during performing security algorithms. New system architecture features, such as larger cache sizes and multicore processors, have increased the prevalence of side channels, in addition to, the availability of measurement apparatuses to an attacker. Thus, software developers must be aware of the potential for side-channel attacks and plan appropriately. In this paper, we propose a software implementation of a hashing method based on SHA3-512 hashing algorithm that can counteract the side-channel attacks. To achieve our goal, we use three techniques, first, we shuffle the dataset, salt, and process selector arrays using "Fisher Yates" algorithm. Second, we use volatile memory objects to hold critical data. Finally, we apply the thread locking technique where at most one thread can access the critical objects at a time. Experimental results show that our proposed hashing method is more secure than other related methods. Although there is a trade-off between hashing security and hashing processing time, the processing time of the proposed hashing method is still acceptable.

The optimisation of a communication system becomes a difficult objective if distinct techniques are utilised to resolve different problems of the same system. Accordingly, the main target of future mobile communication systems (e.g. fifth generation) is to integrate different techniques under a unified framework for the optimisation purpose. This study proposes a downlink air interface that targets maximum capacity and bit error rate (BER) performance enhancement. The proposed system is an integration of a full loaded multi-code transmission orthogonal frequency code division multiple access and space-time spreading that exploits transmit diversity needed for BER enhancement and data rate optimisation. Further BER improvement was achieved through applying an effective iterative interference cancellation in the space domain combined with multi-code interference suppression algorithm at the receiver. The authors present a system performance analysis in addition to simulation results for the proposed system. The BER performance improvement was emphasised through comparing the proposed system with a similar system that uses joint iterative detection. Finally, the effect of frequency domain spreading factor with different number of iteration loops was investigated for further BER system performance enhancement. The achieved BER performance outperforms the maximal ratio receive combining diversity system performance with 1Tx and 8Rx.