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Machine Learning in IoT-Based Ambient Backscatter Communication System
Published in Bhawana Rudra, Anshul Verma, Shekhar Verma, Bhanu Shrestha, Futuristic Research Trends and Applications of Internet of Things, 2022
Shivani Chouksey, Tushar S. Muratkar, Ankit Bhurane, Prabhat Sharma, Ashwin Kothari
IoT is expected to connect billions of devices, bringing digital change to a wide range of industries, including agriculture, homes, and healthcare. Back-Com appeals to a wide range of wireless sensors because it combines energy collection with low-power communication. Backscatter has emerged as a significant competitor for other wireless systems because of its capacity to transmit electricity while also delivering ultra-low power wireless back-haul. Ambient backscatter is a new method of wireless communication with economic promise as well as a number of issues [20]. Ambient backscatter systems enhance the overall IoT architecture in two ways: first, they enable local access the sensors which consume very low power, and second, they work well with large-scale networks and are more reliable as compared to the other wireless IoT systems, at nearly negligible energy and complexity costs [21]. ML methodologies to extract the backscattered signal from the tag to receiver have been studied. The user provides the machine with a known data set with desired inputs and outputs, and the system must figure out how to get to those inputs and outputs in supervised learning, but in unsupervised learning, the machine hunts for patterns in the data. Reinforcement learning can help improve the performance of backscatter networks in ambient Back-Com.
Recent Trends in 5G and Machine Learning, Challenges, and Opportunities
Published in Uzzal Sharma, Parmanand Astya, Anupam Baliyan, Salah-ddine Krit, Vishal Jain, Mohammad Zubair Khan, Advancing Computational Intelligence Techniques for Security Systems Design, 2023
S. Kannadhasan, R. Nagarajan, M. Shanmuganantham
The Internet of Things (IoT), which connects a broad range of devices, is a critical component of 5G mobile communications. Traditional backscatter communication techniques, on the other hand, rely on the reader being able to affect radio frequencies, thus IoT deployment is restricted owing to low power supplies. Ambient backscatter communication, unlike typical backscatter communication (for example, passive sensors and RF identification (RFID) tags), does not need specialized equipment to supply power, instead using RF waves in the environment as both energy and signal resources for reflection. As a consequence, ambient backscatter allows for long-term and self-sustaining connections while lowering device maintenance and deployment expenses. We picked 4G, 5G, and Wireless-Fidelity (Wi-Fi) signals with frequencies in the range of 2–4GHz as the ambient resources since the ambient setup does not need extra spectrum services. There are still a slew of obstacles to overcome. Wireless signals may be used by unauthorized eavesdroppers to acquire information material, and transmissions of the same frequency are overlaid at the receiver to cause interference, making signal identification difficult. As processing power has expanded dramatically, traditional encryption techniques that encrypt data using computationally demanding codec algorithms have progressively failed. The primary idea behind physical layer security is to use the noise's inherent unpredictability to your advantage. The frequency spectrum of ultra-wideband (UWB) is made up of ultra-short bursts in the frequency domain. Working with UWB has the primary goal of obtaining high data rates while being consistent with wireless networking standards.
Enabling Massive IoT in 5G and Beyond Systems: Evolution and Challenges
Published in Zoran S. Bojkovic, Dragorad A. Milovanovic, Tulsi Pawan Fowdur, 5G Multimedia Communication, 2020
Chaochao Yao, Jia You, Gongpu Wang, Yigang Cen
Ambient backscatter is a new communication technology that utilizes ambient wireless signals to enable the tag to communicate with the reader. It can also enable battery-free devices to communicate mutually or connect to the Internet. Accordingly, ambient backscatter can liberate tags and sensors from maintenance-heavy batteries and thus has significant commercial value.
Ambient Backscatter Communications to Energize IoT Devices
Published in IETE Technical Review, 2020
Mudasar Latif Memon, Navrati Saxena, Abhishek Roy, Sukhdeep Singh, Dong Ryeol Shin
Recently, Ambient Backscatter Communications (AmB-Com) has emerged as an interesting solution that can fulfill the energy requirement of the low powered devices [9–11]. AmB-Com works on the principle of RFID technology that enables a device to use passive components for signal transmission instead of active components [12]. AmB-Com enabled passive devices (also known as tags) do not require any analog to digital conversion of signals. Hence, these devices harvest energy from near-by RF signals and can simultaneously reflect the incident signals to modulate their information. The AmB-Com enables researchers to develop battery-free devices that can communicate using nearby RF signals [12].
What is in Store in the March–April 2020 Issue of IETE Technical Review?
Published in IETE Technical Review, 2020
Ambient Backscatter Communications (AmB-Com) is a technique to enable passive IoT devices to harvest power from nearby Radio Frequency (RF) signals. In this survey paper entitled “Ambient Backscatter Communications to Energize IoT Devices”, the authors Mudasar Latif Memon, Navrati Saxena, Abhishek Roy, Sukhdeep Singh and Dong Ryeol Shin discuss various types of ambient RF signals as the source of energy to energize passive IoT devices. They also discuss efficient power transfer schemes for AmB-Com in addition to energy management, resource allocation, and optimization techniques while highlighting the research challenges in AmB-Com.