The rapid growth of multimedia content has created a demand for effective communication systems. Traditional systems treat all pixel values the same while applying compression techniques, eventually significantly losing important information from the image. To address this problem, this paper proposed a saliency-guided semantic communication, where the salient object from each image is separated as Region of interest and Non-Region of Interest, and to make the transmission efficient different compression rates are applied to these regions. The salient and non-salient regions of the image are transmitted and reconstructed at the receiver side. To show the efficacy of the proposed system, numerical simulations are conducted on VOC2012 dataset. The obtained results show the effectiveness of the proposed method in terms of better high Structural Similarity Index Measure, Peak Signal-to-Noise Ratio, lower Mean Square Error and Contrastive Language–Image Pretraining over LTE and 5G channels. Proposed saliency-guided ROI approach delivers a 40% improvement in energy efficiency, and a 37% reduction in average transmitted bits per image over the JPEG baseline transmission.

Owing to the continuous growth of THz absorber, it finds applications in multidimensional fields such as wireless communication, biomedical, military, and defense. These absorbers play a crucial role in RF imaging system design, mutual coupling reduction in antenna array systems, and RCS reduction applications. In this chapter, we begin with defining the THz band, EM wave absorbers, FSS, metamaterial, and impedance matching. Then, we showcase how FSS and metamaterials play a vital role in the design of absorbers. Further, we classify THz absorbers as FSS, resistive sheets, flexible, and graphene-based absorbers showcasing their working principles. Then, we differentiate THz absorber fabrication techniques, including conventional UV lithography and advanced nano-fabrication technology. The chapter concludes by highlighting different types of absorbance measurement techniques such as THz time-domain spectroscopy, waveguide setup, and anechoic chambers in detail, along with their advantages and limitations.

The proliferation of X and Ku band applications in satellite communications, remote sensing, radar systems, and in ever-increasing wireless networks, impels to design of an ultra-wideband reflection-based linear polarization converter. An efficiently designed converter enhances the signal quality in addition to minimizing the interferences in wireless links. Seeing these upcoming myriad number of applications, in this paper, we design and fabricate a lightweight ultra-wideband converter structure by utilizing two 0.15 mm thin FR-4 sheets and a Teflon air-spacer having a thickness of 5.25 mm. Specifically, the top side of the unit cell consists of a diagonally arranged parallel metallic strip printed on thin FR-4 substrate material which is separated by a Teflon spacer with complete metal on the bottom side. To show the efficacy, numerical simulations are performed and the obtained results are validated by fabricating the device in the lab. The experimental and simulation results show that the proposed structure works as a cross-polarizer with a polarization conversion ratio of more than 90% in the C, X, and Ku bands with an operating range of 6.2-16.6 GHz. The measured co-reflection coefficient of the fabricated device completely matched with the simulated reflection coefficient which corroborates with the obtained results. The proposed structure features a sub-wavelength-sized unit cell ((Formula presented.)), which significantly enhances the angular stability of the design. Additionally, it achieves an impressive fractional bandwidth of 91.2% and is characterized by its lightweight structure, making it highly efficient for various applications, such as radiometers and RCS reduction.

Crime prediction is revolutionizing the public safety by equipping law enforcement with data-driven insights. With the recent development in machine learning and deep learning techniques, recently developed tools analyze crime trends and predict the high-risk areas with greater precision. Methods such as spatio-temporal analysis and hybrid models are essential for improving the accuracy and dependability of predictions. Nonetheless, guaranteeing high-quality and uniform data continues to be a vital concern, since incomplete or biased datasets can distort predictions. Moreover, issues of privacy and fairness demand immediate consideration, while the complexity of these models frequently restricts their practical applications. To address these issues, systems that are transparent and comprehensible are essential. For enhancing the system’s reliability, it is also necessary to integrate socio-economic and environmental data. Additionally, crime prediction systems must also be designed to scale efficiently and process the real-time data, and to prevent the misuse and maintaining public trust, designing the ethical frameworks are essential. This paper provides the current state of crime prediction methods, their applications, and challenges. It also identifies gaps and proposes strategies for developing more reliable and ethical systems.

Large Language Models (LLMs) have revolutionized business communication with automated email writing, improved efficiency, and personalization. This paper presents a comparative study of four widely used AI-powered LLMs in business email writing considering the following parameters: formality, readability, grammatical correctness, and word limit. This research compares models such as OpenAI-GPT-4o-mini, Google-Gemini-2.0-Flash, Claude-3.7-Sonnet, and Meta-Llama3-70b in producing professional business emails that fit various scenarios. This work quantitatively compares AI-produced emails by adopting automated scoring. Based on our findings, Google-Gemini-2.0-Flash leads its peers in producing professional, polished, and grammatically correct business communication. This research aims to help professionals choose the most appropriate AI LLM to write effective and contextually relevant emails.

This study introduces an innovative MIMO antenna tailored for 5G millimeter-wave applications. By integrating a rectangular closed loop (RCL) and split-ring resonators (SRRs) with a monopole structure, the design achieves notable enhancement in impedance performance around the 26.5 GHz frequency. The MIMO configuration comprises four radiating elements positioned on a common PCB with a space-efficient footprint of 30 × 30mm2. The developed four-port antenna system offers a wide impedance bandwidth of 2 GHz (25.7-27.7 GHz) centred at 26.5 GHz, achieving a total efficiency of 85-95% over the operating band. Additionally, the antenna exhibits envelope correlation coefficient (ECC) values within acceptable limits, ensuring excellent isolation between the ports. The antenna achieves an average gain of 7 dBi, confirming its effectiveness for deployment in millimeter-wave 5G New Radio (NR) bands n257, n258, and n261.

Seeing the rising applications of metamaterial in sensing and imaging, satellite communications, it becomes evident to design a high-gain microstrip patch antenna. To support these applications, this paper proposes a 7 x 7 array of planar novel metamaterial unit cells used as a superstrate to enhance the gain of microstrip patch antenna operating at 11.2 GHz. This proposed metamaterial structure yields a very low (near zero) value of effective refractive index at 11.2 GHz. Hence, the superstrate behaves as a near zero-indexed-medium (NZIM) around this frequency. NZIM superstrate are very popular because of their ability to focus the radiation and by utilizing this property, a significant gain enhancement has been achieved in the usage of patch antennas. Numerical simulations have been conducted using the CST Microwave studio, and obtained results corroborate that NZIM superstrate when suspended over a microstrip patch antennas significantly improves the gain around the value of 7.5 dB at 11.2 GHz, and efficiency is also improved.

Device-to-device (D2D) communication that allows direct communication between nearby mobile devices without traversing through the base station is a potential solution to solve the problem of safer and faster data rate communication. This review paper comprehensively explores the security aspects of D2D communication, focusing on the vulnerabilities, threats, and existing security mechanisms. In addition, it provides an in-depth analysis of the security challenges in D2D communication, including eavesdropping, data integrity, authentication, and privacy concerns. Furthermore, it also delves into the potential security risks associated with different D2D communication scenarios, such as public safety, proximity-based services, and ad-hoc networking. Toward the end, this survey discusses the open research challenges and future directions in securing D2D communication, highlighting the need for robust security protocols to mitigate the evolving threats in this dynamic communication paradigm. The findings presented in this survey aim to provide researchers, practitioners, and policymakers with a comprehensive understanding of the security landscape in D2D communication, thereby contributing to the successful deployment of secure and reliable D2D communication systems.

The exponential increase in video data demands over the wireless network has created the interest among the researchers to come up with a potential solution to efficiently distribute the video content over 5G and beyond networks. Therefore, in this paper, an energy-efficient scheme for video content dissemination by utilizing the device-to-device (D2D) communication has been proposed. The work aims to address the twin issues of energy efficiency and distortion minimization simultaneously. In the current cellular networks, every user downloads the video independently which often leads to low quality as the distance between the base station (BS) and mobile device increases. In the proposed scheme, proximate mobile nodes are grouped into clusters and among them a cluster head is chosen which forwards the data to cluster members using D2D communication. To make the system more spectral efficient, performance of the proposed scheme is evaluated in underlay mode where D2D links are sharing the channels with the primary cellular users. To show the efficacy of the proposed scheme, numerical analysis is conducted, and results show that significant energy saving can be achieved with the proposed scheme as compared to the conventional multicasting scheme, and it also provides improved video quality with lesser distortion and delay.

We address the problem of distributed resource allocation for multicast communication in device-to-device (D2D) enabled underlay cellular networks. The optimal resource allocation is crucial for maximizing the performance of such networks, which are limited by the severe co-channel interference between cellular users (CU) and D2D multicast groups. However, finding such optimal allocation for networks with a large number of CUs and D2D users is challenging. Therefore, we propose a pragmatic scheme that allocates resources distributively, reducing signaling overhead and improving network scalability. Numerical simulations establish the efficacy of the proposed solution in improving the overall system throughout, compared to various existing schemes.

This paper considers a device-to-device (D2D) communication-enabled multi-cell massive multi-input multi-output (MIMO) system, where multiple D2D pairs reuse the pilot signal allocated to the cellular users. The closed-form expressions for the spectral efficiency and its lower-bounds are derived using maximal ratio combining. To closely model the channel in the practical environment, a combination of line-of-sight (LoS) path and a stochastic non-line-of-sight (NLoS) component describing a spatially correlated multipath environment is considered. To characterize the achieved spectral efficiency for considered channel modeling, simulations are performed. The obtained results show that the system performance achieved with the Rician correlated fading is higher than the spectral efficiency achieved with Rayleigh-fading.

In this paper, a graph and matrix theory-based network selection scheme is proposed for overlapping wireless networks which comprises of WiFi/WiMAX/LTE technologies. The parameters data rate, service cost, delay, and power consumption have been taken into account. A graph and corresponding matrix is constructed by considering the above parameters and their relative importance for a particular application. Then, a 'network satisfaction value' is determined by computing the permanent of matrix. This value is used to select the optimal access point. In comparison to conventional received signal strength indicator (RSSI) based schemes, improved results have been obtained owing to the proposed graph-based selection mechanism. The results are also compared with those of other existing schemes like TOPSIS (techniques for order preference by similarity to ideal solution), result shows that the proposed scheme is able to select most suitable network according to user preferences, and also reduce the number of handoffs.

This paper considers a cooperative cognitive radio network with two primary users (PUs), and two secondary users (SUs) that enables two-way communications of primary, and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information, and power transfer (SWIPT). With the considered network, SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs. The overall bidirectional end-to-end transmission takes place in four phases, which include both energy harvesting (EH), and information transfer. A non-linear energy harvester with a hybrid SWIPT scheme is adopted in which both power-splitting, and time-switching EH techniques are used. The SUs aid in relay cooperation by performing an amplify-and-forward operation, whereas selection combining technique is adopted at the PUs to extract the intended signal from multiple received signals broadcasted by the SUs. Accurate outage probability expressions for the primary, and secondary links are derived under the Nakagami-m fading environment. Further, the system behavior is analyzed with respect to achievable system throughput, and energy efficiency. Since the performance of the considered system is strongly affected by the spectrum sharing factor, and hybrid SWIPT parameters, particle swarm optimization is implemented to optimize the system parameters so as to maximize the system throughput, and energy efficiency. Simulation results are provided to corroborate the performance analysis, and give useful insights into the system behavior concerning various system/channel parameters.

In this letter, we investigate the performance of wireless powered cognitive radio sensor networks (CRSNs) in the presence of hardware impairments (HIs). Wireless powered CRSN can be a potential solution to address spectrum scarcity and power shortage in the wireless sensor networks. Herein, the spectrum sharing is exploited to compensate for the spectrum scarcity, whereas the radio frequency energy harvesting technique is utilized to prolong the lifetime. Specifically, we consider a CRSN scenario with two primary nodes and a pair of sensor nodes (SNs). The SNs are assumed to be low-cost devices in view of the Internet of Things infrastructure. Consequently, they are more prone to suffer from different HIs. For evaluating the system performance, we obtain accurate expressions of the outage probability and the system throughput over Nakagami-m fading in the presence of transceiver HIs.

Underlay in-band device-To-device (D2D) multicast communication, where same content is disseminated via direct links in a group, has potential to improve the spectral and energy efficiencies of cellular networks. However, existing resource allocation techniques may not work well for multicast in next generation wireless networks with many simultaneously connected devices. To address this problem, we focus on channel allocation algorithms where multiple D2D multicast groups (MGs) share the channel with a cellular user (CU). The objective is to maximize the sum throughput of CUs and D2D multicast groups, while ensuring a certain level of quality of service (QoS) to CUs and D2D MGs. Our main contributions are the exact calculation of outage probability experienced by a D2D receiver in the multicast group and a scheme to share channels among D2D MGs and CUs by minimizing these probabilities. Numerical results demonstrate the impact on the sum throughput of the number of MGs sharing the channel with a CU, geographical spread of MGs, and the maximum transmit power of cellular users.

Underlay in-band device-to-device (D2D) multicast communication, where the same content is disseminated via direct links in a group, has the potential to improve the spectral and energy efficiencies of cellular networks. However, most of the existing approaches for this problem only address either spectral efficiency (SE) or energy efficiency (EE). We study the tradeoff between SE and EE in a single cell D2D integrated cellular network, where multiple D2D multicast groups (MGs) may share the uplink channel with multiple cellular users. We explore SE-EE tradeoff for this problem by formulating the EE maximization problem with constraint on SE and maximum available transmission power. A power allocation algorithm is proposed to solve this problem and its efficacy is demonstrated via extensive numerical simulations. The tradeoff between SE and EE as a function of density of D2D MGs, and maximum transmission power of an MG is characterized.

Device-to-device (D2D) multicast communication is considered as a potential solution to improve the spectral efficiency of cellular networks. This paper focuses on resource allocation in underlay D2D multicast networks where multiple D2D multicast groups (MGs) share the uplink frequency channels with multiple cellular users (CUs). An optimization problem that maximizes the system throughput while fulfilling the maximum power constraint of every mobile user and ensuring a certain level of quality of service (QoS) to every CU and D2D multicast group is formulated. This formulation leads to mixed integer non-linear programming (MINLP), which is computationally intractable for large scale networks. Therefore, to find a feasible solution, we propose a channel sharing algorithm which determines how many MGs can share a channel with certain QoS guarantees to CU and D2D MGs. Then, we propose a power allocation algorithm that maximizes the system throughput while satisfying the various constraints. The impact of geographical spread of MGs, number of MGs, maximum available transmission power, and QoS requirements of every CU on achievable system throughput is analyzed. Numerical results show the efficacy of proposed model in terms of D2D MG's throughput and spectrum efficiency.

Device-To-Device (D2D) multicast communication is emerging as a practical solution for alleviating severe capacity crunch in data-centric wireless networks and encourage backhaul-free communication directly among devices with similar content requirement. To exploit D2D communication for achieving higher throughput, less delay and efficient spectrum usage, a careful resource allocation is required. In this study, we analyze the resource sharing between cellular users (CUs) and D2D users when one or more than one D2D multicast groups share the resources with a CU, with the objective of maximizing the system throughput and spectrum efficiency, while guaranteeing a certain level of quality of service to CUs and D2D users.

Device-to-Device (D2D) multicast communication is emerging as a practical solution to alleviate severe capacity crunch in data-centric wireless networks and to encourage backhaul-free communication directly among devices with similar content requirement. Resource allocation in multicast networks is a critical issue that impacts both, the network throughput and spectrum efficiency. We devise an uplink resource reuse strategy for multiple multicast D2D groups and multiple cellular users (CUs), with the objective of maximizing the sum throughput, while guaranteeing a certain level of quality of service (QoS) to CUs and D2D users. We establish the efficacy of the proposed scheme for variable group sizes and geographical spread.

The potential of device-to-device (D2D) technology to support multicast services in LTE-Advanced networks has been recently realized. D2D communication brings great benefits to cellular networks in terms of enhanced spectral efficiency and larger coverage by enabling the devices to communicate directly with each other. D2D communication may lead to improved network capacity by sharing resources with cellular users (CUs). However, the resulting mutual interference may decrease or even outweigh the gain of D2D communication. In this paper, we propose a scheme to minimize the interference among D2D and CUs through a resource allocation scheme. We formulate the uplink resource allocation problem where a D2D multicast group can reuse resources of CUs under the constraint that the signal to interference plus noise ratio (SINR) requirements of CUs and D2D users are satisfied. We analyze a joint power and channel allocation scheme to maximize the total throughput of CUs and D2D users. The performance of D2D communication depends on maximum power constraint for the D2D users. Simulation results establish the efficacy of the proposed scheme.

In relay-assisted cellular networks, relay nodes are usually deployed in a cellular cell without taking the information about the place where it needs to be deployed. So sometime it will ultimately leads to wastage of resources. In this paper, we have focused on this problem and proposed a fuzzy-based methodology to find the optimum quantity and requirement of these relay nodes in cellular networks. Proposed methodology tackles with two problems, which are “where to deploy,” “how many relay nodes to deploy.” In cellular cell, users residing near the base station get higher data services and users residing near the boundary of cellular cell get lower data services. So this introduces unfairness for far users in terms of data rate. Relay-assisted networks are introduced to solve this problem. As the number of users is increasing day by day, so it is necessary to provide adaptive positioning of relay nodes for getting optimal services within limited infrastructure cost. In other words, relay-assisted cellular networks should be adaptive for traffic offered by specific area. In this paper, we have taken three parameters that strongly affect the position of relay nodes. These three parameters include user density in specific area, amount of high-speed data requirement from a certain area on regular basis and signal strength to tackle with dead zones over the entire cellular cell.