Integrated sensing and communication (ISAC) has received significant attention over the past five years as a key component of the 6G vision for next-generation communication systems. Starting with the fundamentals of ISAC, we present strategies focused on sensing-centric and communication-centric ISAC systems that satisfy both radar and communication objectives using the same physical hardware and waveform. The communication-centric ISAC focuses primarily on improving communication performance beyond 5G/6G cellular networks andWi-Fi standards, while also performing additional processing required for detection. On the other hand, the sensing-centric ISAC prioritizes sensing and detection capabilities while incorporating communication functions in the most efficient way possible. In this survey, we present a comprehensive review of both ISAC systems along with new approaches for enabling technologies and highlight unique challenges and existing solutions that are already available. We explore the roles of innovative functions in enabling ISAC, including joint waveform design, edge computing, vehicular sensing and communications, and their practical applications. We then discuss 3GPP standardization efforts related to ISAC as a future direction for the 6G vision. We also outline possible future research directions, with a specific emphasis on security, artificial intelligence, and machine learning.

Drone base stations (DBSs) have received significant research interest in recent years. They provide a flexible and cost-effective solution to improve the coverage, connectivity, quality of service (QoS), and energy efficiency of large-area Internet of Things (IoT) networks. However, as DBSs are costly and power-limited devices, they require an efficient scheme for their deployment in practical networks. This work proposes a realistic mathematical model for the joint optimization problem of DBS placement and IoT users’ assignment in a massive IoT network scenario. The optimization goal is to maximize the connectivity of IoT users by utilizing the minimum number of DBS, while satisfying practical network constraints. Such an optimization problem is NP-hard, and the optimal solution has a complexity exponential to the number of DBSs and IoT users in the network. Furthermore, this work also proposes a linearization scheme and a low-complexity heuristic to solve the problem in polynomial time. The simulations are performed for a number of network scenarios, and demonstrate that the proposed heuristic is numerically accurate and performs close to the optimal solution.

Wireless transmission systems of Implantable Medical Devices (IMD)GCs should be secure against GCtoeavesdroppers and adversaries because of patient rights and health. This study focuses on full-duplex secure communication of wireless IMD systems, proposing a new protector that is compatible with existing unsecure systems. This new protector is GCan externally worn jacket and, therefore, called Security Jacket. GCHowever,Because some advanced sensors are placed on the jacket to provide physical layer security. Randomly multi-jamming GCand extractionwith a great number of sensors is applied when IMD transmission occurs with the GCjamming extraction and Maximum Ratio Combining (MRC) reception simultaneously. When reception by IMD GCareis performed, a randomized spoofing-based transmit beamforming technique is applied. This protector also supports higher power efficiency and longer battery life.

Massive multiple-input multiple-output (MIMO) is still valid as an important system to increase performance of fifth generation (5G) and beyond wireless communication technologies. Spectrum efficiency (SE), high data rate and energy efficiency (EE) are among these performances. Recently, due to the increase in interconnected devices, the spread of internet of things (IoT) systems and the limited resources, various performance improvements have become inevitable. It is seen that there are various studies to realize such improvements with Massive MIMO. There are many researches especially for spectrum efficiency and energy efficiency. Because issue of energy and bandwidth problem are among the issues that need to be solved and developed first. In recent years, it is understood that power allocation algorithms have been focused on solving these two problems. In this study, researches on power allocation algorithms for MIMO systems are examined. The main points of the studies are emphasized. In addition, the comparison of three different power allocation algorithms, which will be among the basic power allocation algorithms, are carried out in terms of spectrum efficiency. Çok büyük çok girişli çok çıkışlı sistem (Massive MIMO) beşinci nesil (5G) ve ötesi kablosuz iletişim teknolojilerinin performanslarını geliştirmek için önemli bir sistem olarak hala geçerliliğini korumaktadır. Spektrum verimliliği (SE), enerji verimliliği (EE) bu performanslar arasındadır. Son zamanlarda birbirleriyle bağlantılı cihazların artması, internet of things (IoT) sistemlerin gün geçtikçe yayılması ve buna rağmen kaynakların sınırlı olmasından dolayı çeşitli performans geliştirmeleri kaçınılmaz olmuştur. Massive MIMO ile birlikte bu tür iyileştirmeleri gerçekleştirmek için çeşitli çalışmaların olduğu görülmektedir. Özellikle spektrum verimliliği ve enerji verimliliği için birçok araştırmalar mevcuttur. Çünkü enerji konusu ve bant genişliği problemi ilk olarak çözülmesi ve geliştirilmesi gereken konular arasındadır. Son yıllarda bu iki problemin çözümüne yönelik güç tahsisi algoritmalarına odaklanıldığı anlaşılmaktadır. Bu çalışmada, güç tahsisi algoritmaları hakkındaki araştırmalar incelenmiştir. Çalışmaların temel noktaları üzerinde durulmuştur. Ayrıca temel güç tahsisi algoritmaları arasında yer alacak üç farklı güç tahsisi algoritmasının birbirleri arasında kıyaslaması spektrum verimliliği açısından gerçekleştirilmiştir.

Wireless Sensor Networks (WSNs) based on Internet of Things (IoT) applications are increasing day by day. These applications include healthcare, infrastructure monitoring, smart homes, wearable devices and smart cars. However, considering the fact that many different application areas will emerge in next generation wireless communication systems, efficient use of frequency spectrum is important. Because the whole frequency spectrum is now very crowded, it is important to ensure maximum spectrum efficiency for effective WSNs based on IoT. This study sought to determine which mode more effectively achieves spectrum efficiency for the performance of effective IoT systems under given conditions with respect to the length of the pilot sequence, Time Division Duplexing (TDD) or Frequency Division Duplexing (FDD). The results were obtained by Monte Carlo simulations. To the best of our knowledge, a study of effective mode selection analysis for spectrum efficiency in IoT based systems has not been available in the literature yet. The results of this study are useful for determining the appropriate design conditions for WSNs based on IoT.