613 research outputs found
A survey of symbiotic radio: Methodologies, applications, and future directions
The sixth generation (6G) wireless technology aims to achieve global connectivity with environmentally sustainable networks to improve the overall quality of life. The driving force behind these networks is the rapid evolution of the Internet of Things (IoT), which has led to a proliferation of wireless applications across various domains through the massive deployment of IoT devices. The major challenge is to support these devices with limited radio spectrum and energy-efficient communication. Symbiotic radio (SRad) technology is a promising solution that enables cooperative resource-sharing among radio systems through symbiotic relationships. By fostering mutualistic and competitive resource sharing, SRad technology enables the achievement of both common and individual objectives among the different systems. It is a cutting-edge approach that allows for the creation of new paradigms and efficient resource sharing and management. In this article, we present a detailed survey of SRad with the goal of offering valuable insights for future research and applications. To achieve this, we delve into the fundamental concepts of SRad technology, including radio symbiosis and its symbiotic relationships for coexistence and resource sharing among radio systems. We then review the state-of-the-art methodologies in-depth and introduce potential applications. Finally, we identify and discuss the open challenges and future research directions in this field
Relaying in the Internet of Things (IoT): A Survey
The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to gateways. However, incorporating relays into IoT networks faces some challenges. IoT end devices are designed primarily for uplink communication of small-sized observations toward the network; hence, opportunistically using end devices as relays needs a redesign of both the medium access control (MAC) layer protocol of such end devices and possible addition of new communication interfaces. Additionally, the wake-up time of IoT end devices needs to be synchronized with that of the relays. For cellular-based IoT, the possibility of using infrastructure relays exists, and noncellular IoT networks can leverage the presence of mobile devices for relaying, for example, in remote healthcare. However, the latter presents problems of incentivizing relay participation and managing the mobility of relays. Furthermore, although relays can increase the lifetime of IoT networks, deploying relays implies the need for additional batteries to power them. This can erode the energy efficiency gain that relays offer. Therefore, designing relay-assisted IoT networks that provide acceptable trade-offs is key, and this goes beyond adding an extra transmit RF chain to a relay-enabled IoT end device. There has been increasing research interest in IoT relaying, as demonstrated in the available literature. Works that consider these issues are surveyed in this paper to provide insight into the state of the art, provide design insights for network designers and motivate future research directions
Coexistence of RF-powered IoT and a Primary Wireless Network with Secrecy Guard Zones
This paper studies the secrecy performance of a wireless network (primary
network) overlaid with an ambient RF energy harvesting IoT network (secondary
network). The nodes in the secondary network are assumed to be solely powered
by ambient RF energy harvested from the transmissions of the primary network.
We assume that the secondary nodes can eavesdrop on the primary transmissions
due to which the primary network uses secrecy guard zones. The primary
transmitter goes silent if any secondary receiver is detected within its guard
zone. Using tools from stochastic geometry, we derive the probability of
successful connection of the primary network as well as the probability of
secure communication. Two conditions must be jointly satisfied in order to
ensure successful connection: (i) the SINR at the primary receiver is above a
predefined threshold, and (ii) the primary transmitter is not silent. In order
to ensure secure communication, the SINR value at each of the secondary nodes
should be less than a predefined threshold. Clearly, when more secondary nodes
are deployed, more primary transmitters will remain silent for a given guard
zone radius, thus impacting the amount of energy harvested by the secondary
network. Our results concretely show the existence of an optimal deployment
density for the secondary network that maximizes the density of nodes that are
able to harvest sufficient amount of energy. Furthermore, we show the
dependence of this optimal deployment density on the guard zone radius of the
primary network. In addition, we show that the optimal guard zone radius
selected by the primary network is a function of the deployment density of the
secondary network. This interesting coupling between the two networks is
studied using tools from game theory. Overall, this work is one of the few
concrete works that symbiotically merge tools from stochastic geometry and game
theory
Energy-efficient non-orthogonal multiple access for wireless communication system
Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed
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