مقاله انگلیسی تخصیص عادلانه قدرت در سیستمهای شناختی تعاونی برای شبکههای IoT آینده
Abstract
Keywords
1. Introduction
2. System model and problem formulation
3. Proposed scheme
4. Simulation results
5. Conclusion
Declaration of Competing Interest
Acknowledgment
References
Abstract
To support the massive connectivity in Internet of Things (IoT), several promising techniques like cognitive radio (CR) and non-orthogonal multiple access (NOMA) enables the user to share spectrum resources. This work aims to achieve fairness among secondary users (SUs) in IoT cooperative NOMA-based CR transmission. We design a power allocation algorithm, an independent battery constraint at each node is considered, and power gap among transmissions of two NOMA users is applied for successive interference cancellation. The simulation results show that the proposed framework provides excellent performance and for sufficient available transmission power perfect fairness is achieved.
1. Introduction
The use of orthogonal multiple access (OMA) systems is well known because of their excellent performance [1], [2], [3]. However, the Internet of Things (IoT) demands high spectral efficiency (SE) which the OMA systems are unable to provide [4], [5]. Hence, researchers have recently been working on finding a better multiple access substitute. Non-orthogonal multiple access (NOMA) provides better performance as compared to OMA and is a potential candidate for the IoT systems [6], [7]. NOMA offers high spectral efficiency because it enables multiple IoT users to simultaneously share a single channel [8]. This can be accomplished by superimposing multiple signals at the transmitter side using the superposition coding technique and then successfully decode it at the receiver side with the help of successive interference cancellation technique (SIC) [9]. This can be accomplished by superimposing multiple signals at the transmitter side using the superposition coding technique and then successfully decode it at the receiver side with the help of successive interference cancellation technique (SIC) [9]. Another network that provides high spectral efficiency by employing spectrum reuse is cognitive radio (CR) [10]. In the CR systems, the unlicensed secondary users (SUs) share the channels of the licensed primary users (PUs) [11].
In the advanced communication networks, optimization becomes necessary to obtain the desired performance [12], [13]. Energy efficiency is one of the most important issues in various emerging network technologies [14], [15], [16]. Optimal power allocation is very important to enhance the performance of the communication networks [17], [18]. Thus, in the literature the problem of power optimization for NOMA and CR based systems have been considered many times. In [19], the power allocation was optimized such that the rate demand of each user is satisfied. The authors in [20] proposed a power optimizing framework for maximizing the energy efficiency of NOMA networks. The problem of secrecy rate maximization in NOMA was studied in [21]. Then, the authors in [22] optimized power loading for rate maximization in NOMA networks. However, the results showed that the designed framework sacrifices user-fairness to increase the sum rate of the system. Hence, a sequential quadratic programming based framework was proposed in [23] to achieve fairness in the rates of all the users in a NOMA system.