Power Allocation for Cognitive Radio Networks Employing Non-Orthogonal Multiple Access

Zeng, Ming; Tsiropoulos, Georgios I.; Dobre, Octavia A.; Ahmed, Mohamed H.

doi:10.1109/glocom.2016.7842156

Cited by 58 publications

(27 citation statements)

References 12 publications

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“…They take user power control and SIC implementation into account to solve the power and channel allocation problem. Power allocation in NOMA-based cognitive radio networks [63] is also an unexplored area of research.…”

Section: Resource Allocationmentioning

confidence: 99%

Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges

Islam

Avazov

Dobre

et al. 2017

IEEE Commun. Surv. Tutorials

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2,043

1,162

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Abstract-Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for performance enhancement in next-generation cellular communications. Compared to orthogonal frequency division multiple access (OFDMA), which is a well-known high-capacity orthogonal multiple access (OMA) technique, NOMA offers a set of desirable benefits, including greater spectrum efficiency. There are different types of NOMA techniques, including power-domain and code-domain. This paper primarily focuses on power-domain NOMA that utilizes superposition coding (SC) at the transmitter and successive interference cancellation (SIC) at the receiver. Various researchers have demonstrated that NOMA can be used effectively to meet both network-level and user-experienced data rate requirements of fifth-generation (5G) technologies. From that perspective, this paper comprehensively surveys the recent progress of NOMA in 5G systems, reviewing the state-of-the-art capacity analysis, power allocation strategies, user fairness, and user-pairing schemes in NOMA. In addition, this paper discusses how NOMA performs when it is integrated with various proven wireless communications techniques, such as cooperative communications, multiple-input multiple-output (MIMO), beamforming, space-time coding, and network coding, among others. Furthermore, this paper discusses several important issues on NOMA implementation and provides some avenues for future research. I. INTRODUCTIONFrom analog phone calls through to all Internet Protocol services, including voice and messaging, each transition has been encouraged by the need to meet the requirements of the new generation of mobile technology. Subsequently, mobile communications technology is presently facing a new challenge, giving birth to a hyper-connected society through the emergence of fifth-generation (5G) services. With enormous potential for both consumers and industry, 5G is expected to roll out by 2020. From the next-generation radio access technology viewpoint, a step change in data speed and a significant reduction in end-to-end latency is a major concern for 5G, since the rapid development of the mobile Internet and the Internet of Things (IoT) exponentially accelerates the demand for high data-rate applications. In particular, many of the industry initiatives that have progressed with work on 5G declare that the network-level data rate in 5G should be 10-20 Gbps (that is, 10-20 times the peak data rate in 4G), and the user-experienced data rate should be 1 Gbps (100 times the user-experienced data rate in 4G). They also set the latency (end-to-end round-trip delay) at 1 millisecond (one-fifth of the latency in 4G).The underlying physical connection in a cellular network is called radio access technology, which is implemented by a radio access network (RAN). A RAN basically utilizes a channel access technique to provide the mobile terminals with a connection to the core network. The design of a suitable multiple access technique is one of the most important aspects in improvi...

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Section: Resource Allocationmentioning

confidence: 99%

Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges

Islam

Avazov

Dobre

et al. 2017

IEEE Commun. Surv. Tutorials

Self Cite

2,043

1,162

View full text Add to dashboard Cite

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“…Operation mechanism [7] SISO CR with NOMA Underlay [8] MIMO CR with NOMA Underlay [9] Large-scale CR with NOMA Underlay [10] Cooperative CR with NOMA Overlay [11] Cooperative multicast CR with NOMA Overlay [12] Cooperative CR with NOMA and STBC Overlay [13] MISO CR with NOMA √ Underlay [14] SISO CR with NOMA √ Underlay be inactive, otherwise it continues performing spectrum sensing in order to find available frequency bands.…”

Section: Resource Optimizationmentioning

confidence: 99%

“…The simulation results have shown that NOMA can achieve EE gains in underlay CRNs compared with OMA. The authors in [14] designed an optimal power allocation strategy for the underlay CRNs with NOMA. Moreover, the characteristic of NOMA was exploited to design the optimal power allocation algorithm.…”

Section: A Resource Optimization In Crns With Nomamentioning

confidence: 99%

State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA

Zhou

Liang

et al. 2018

IEEE Wireless Commun.

199

124

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The explosive growth of mobile devices and the rapid increase of wideband wireless services call for advanced communication techniques that can achieve high spectral efficiency and meet the massive connectivity requirement. Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are envisioned to be important solutions for the fifth generation wireless networks. Integrating NOMA techniques into CR networks (CRNs) has the tremendous potential to improve spectral efficiency and increase the system capacity. However, there are many technical challenges due to the severe interference caused by using NOMA. Many efforts have been made to facilitate the application of NOMA into CRNs and to investigate the performance of CRNs with NOMA. This article aims to survey the latest research results along this direction. A taxonomy is devised to categorize the literature based on operation paradigms, enabling techniques, design objectives and optimization characteristics. Moreover, the key challenges are outlined to provide guidelines for the domain researchers and designers to realize CRNs with NOMA. Finally, the open issues are discussed.Cognitive radio, non-orthogonal multiple access, spectral efficiency, massive connectivity. I. INTRODUCTIONT HE explosive growth of mobile devices, the rapidly increasing demand on the broadband and highrate communication services, such as augmented reality (AR) and virtual reality (VR), and the fixed spectrum assignment policy result in the increasingly severe spectrum scarcity problem. According to the third Generation Partnership Project (3GPP), compared with the fourth generation (4G) networks, the fifth generation (5G) networks are required to achieve 1000 times higher system capacity, 10 times higher spectral efficiency (SE), and 100 times higher connectivity density [1]. Moreover, among these requirements, meeting the system capacity is the most important but probably the most challenging one due to the limited spectrum resource. Thus, it is imperative to develop advanced communication techniques that can achieve high SE as well as massive wireless connectivity. As a promising technique, cognitive radio (CR) has drawn significant attention in both industry and academia due to its high SE [2]. It can enable the secondary network (or called the unlicensed network) to access the licensed frequency bands of the primary network by using adaptive transmission strategies while protecting the quality-of-service (QoS) of the primary one.Besides CR, non-orthogonal multiple access (NOMA) techniques are promising to improve SE and user connectivity density [4], [5]. Unlike the conventional orthogonal multiple access (OMA) techniques, NOMA techniques allow multiple users simultaneously access the network at the same time and the same frequency band by using non-orthogonal resources, such as different power levels or low-density spreading codes. In [5], the authors have classified the existing dominant NOMA schemes into two categories based on the non-orthogonality resources, namely, power-...

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“…The scheduling and power allocation algorithm that solves the optimization problem is compared to the fractional transmit power control algorithm and shown to improve performance for the user with stronger channel, while performance is not always improved for the user with weaker channel. The work in [15] uses a new algorithm to solve the cognitive radio NOMA power allocation problem which can outperform the fractional transmit power algorithm for admitting secondary users into the network. In [16], the authors seek to optimize the sum-rate of a multi-user downlink NOMA system by using a constraint based on the total power allocated to the signals at each SIC stage, and its relation to the minimum required rate for each signal to be decoded.…”

Section: Previous Work and Current Contributionmentioning

confidence: 99%

Fundamentals of Power Allocation Strategies for Downlink Multi-User NOMA With Target Rates

Oviedo

Sadjadpour

2020

IEEE Trans. Wireless Commun.

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For downlink multi-user non-orthogonal multiple access (NOMA) systems with successive interference cancellation (SIC) receivers, and a base-station not possessing the instantaneous channel gains, the fundamental relationship between the target rates and power allocation is investigated. It is proven that the total interference from signals not removed by SIC has a fundamental upper limit which is a function of the target rates, and the outage probability is one when exceeding this limit. The concept of well-behaved power allocation strategies is defined, and its properties are proven to be derived solely based on the target rates. The existence of power allocation strategies that enable NOMA to outperform OMA in per-user outage probability is proven, and are always well-behaved for the case when the outage probability performance of NOMA and OMA are equal for all users. The proposed SIC decoding order is then shown to the most energy efficient. The derivation of wellbehaved power allocation strategies that have improved outage probability performance over OMA for each user is outlined. Simulations validate the theoretical results, demonstrating that NOMA systems can always outperform OMA systems in outage probability performance, without relying on the exact channel gains.

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Power Allocation for Cognitive Radio Networks Employing Non-Orthogonal Multiple Access

Cited by 58 publications

References 12 publications

Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges

Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges

State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA

Fundamentals of Power Allocation Strategies for Downlink Multi-User NOMA With Target Rates

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