Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

Thirunavukkarasu, Manimekalai; Joan, Sparjan Romera; Thangavelu, Laxmikandan

doi:10.4218/etrij.2019-0265

Cited by 18 publications

(6 citation statements)

References 45 publications

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“…All interference constraints of the primary network, including PR i , P S ≤ I i =g SP i [21], must also be satisfied. Therefore, P S is optimally set as P S ¼ min P max , I 1 =g SP 1 , À…”

Section: System Modelmentioning

confidence: 99%

“…Under the operation conditions of the underlay cognitive radio network, the transmit power of the secondary source S (denoted by

P_{S}

) cannot exceed the maximum power (denoted by

P_{\max}

); that is,

P_{S} \leq P_{\max}

. All interference constraints of the primary network, including

{PR}_{i}, P_{S} \leq I_{i} false/ g_{{SP}_{i}}

[21], must also be satisfied. Therefore,

P_{S}

is optimally set as

P_{S} = \min ((), P_{\max}, I_{1} false/ g_{{SP}_{1}}, I_{2} false/ g_{{SP}_{2}}, \dots, I_{M} false/ g_{{SP}_{M}})

[38] where

g_{{SP}_{i}} = {|h_{{normalSP}_{i}}|}^{2}

and

i = \{1,2, \dots, M\}

.…”

Section: System Modelmentioning

confidence: 99%

“…Cognitive radio is a spectrum-sharing solution between primary users in primary networks and secondary users in secondary networks, allowing the efficient use of licensed spectra in primary networks. By selecting one of the sharing protocols (interweave, overlay, or underlay), the secondary users can adaptably and knowledgeably exploit the licensed spectra, guaranteeing that the quality of service of the primary networks is within a given threshold [17,20,21].…”

mentioning

confidence: 99%

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Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

Duy¹,

Tuan

Huynh

2022

ETRI Journal

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We propose short packet communication in an underlay cognitive radio network assisted by an intelligent reflecting surface (IRS) composed of multiple reconfigurable reflectors. This scheme, called the IRS protocol, operates in only one time slot (TS) using the IRS. The IRS adjusts its phases to give zero received cumulative phase at the secondary destination, thereby enhancing the end‐to‐end signal‐to‐noise ratio. The transmitting power of the secondary source is optimized to simultaneously satisfy the multi‐interference constraints, hardware limitations, and performance improvement. Simulation and analysis results of the average block error rates (BLERs) show that the performance can be enhanced by installing more reconfigurable reflectors, increasing the blocklength, lowering the number of required primary receivers, or sending fewer information bits. Moreover, the proposed IRS protocol always outperforms underlay relaying protocols using two TSs for data transmission, and achieves the best average BLER at identical transmission distances between the secondary source and secondary destination. The theoretical analyses are confirmed by Monte Carlo simulations.

show abstract

Section: System Modelmentioning

confidence: 99%

“…Under the operation conditions of the underlay cognitive radio network, the transmit power of the secondary source S (denoted by

P_{S}

) cannot exceed the maximum power (denoted by

P_{\max}

); that is,

P_{S} \leq P_{\max}

. All interference constraints of the primary network, including

{PR}_{i}, P_{S} \leq I_{i} false/ g_{{SP}_{i}}

[21], must also be satisfied. Therefore,

P_{S}

is optimally set as

P_{S} = \min ((), P_{\max}, I_{1} false/ g_{{SP}_{1}}, I_{2} false/ g_{{SP}_{2}}, \dots, I_{M} false/ g_{{SP}_{M}})

[38] where

g_{{SP}_{i}} = {|h_{{normalSP}_{i}}|}^{2}

and

i = \{1,2, \dots, M\}

.…”

Section: System Modelmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

Duy¹,

Tuan

Huynh

2022

ETRI Journal

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show abstract

“…In Reference 26, a near‐optimal user‐grouping and power allocation algorithms were considered for an OFDMA‐NOMA CR system with fixed sub‐channel allocation. A throughput maximization problem in a hybrid OFDMA‐NOMA cooperative CR‐based system was formulated and solved in Reference 27. In Reference 28, a resource allocation technique was developed aiming to extend the network lifetime in OFDMA‐NOMA CR‐based IoT networks subject to achieving predefined QoS constraints.…”

Section: Introductionmentioning

confidence: 99%

Joint bandwidth and power resource allocation technique in multi‐carrier non‐orthogonal multiple access‐based cognitive Internet of Things networks

Al‐Obiedollah

Arabiat

Al-Ajlouni

et al. 2022

Trans Emerging Tel Tech

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The recent development of the Internet of Things (IoT) devices offers an intelligent concept for integrating massive number of interconnected wireless devices. However, supporting such massive number of IoT connections (hundreds of billions) requires an efficient and dynamic spectrum access strategy. Accordingly, the integration of non‐orthogonal multiple access (NOMA) in the cognitive radio (CR) systems, referred to as a multi‐carrier NOMA CR‐enabled system, is envisioned as a potential spectrum‐efficient networking paradigm that can support massive energy‐efficient IoT connectivity in B5G networks while maintaining the quality of services (QoS) of the IoT devices. However, the power consumption issue of the multi‐carrier NOMA CR‐based system becomes as one of key challenges, especially when considering the expected massive connectivity. Accordingly, several power‐aware optimization frameworks have been considered to address this issue. While most of the existing CR‐based multi‐carrier NOMA power allocation mechanisms only optimize the allocated per‐user power, this article proposes a novel joint bandwidth and power allocation problem over each available idle channel with the aim of minimizing the overall transmission power under a set of QoS constrains. Specifically, the bandwidth of each channel is adaptively subdivided into two variable‐width sub‐channels, each is capable to serve a group of CR users using power‐domain NOMA. This novel design is formulated as a joint optimization problem that is shown to be a non‐convex. Therefore, an iterative algorithm with a second‐order cone programming is deployed to handle the non‐convexity of the problem, and thus, determine the solution of it. Simulation results reveal that the developed variable bandwidth adaptive power allocation mechanism outperforms the conventional equal sub‐channel allocation in terms of the required transmission power, which significantly improves the energy efficiency in the system.

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“…Various studies have been conducted to investigate the performance of NOMA networks [2]. To expand the coverage and further improve the system performance, cooperative NOMA has been proposed [3,4]. One research type considers the "strong" NOMA users as relays to help the "weak" users.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of SWIPT‐assisted adaptive NOMA/OMA system with hardware impairments and imperfect CSI

et al. 2022

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This paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT‐assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy‐constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed‐form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI.

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Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

Cited by 18 publications

References 45 publications

Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

Joint bandwidth and power resource allocation technique in multi‐carrier non‐orthogonal multiple access‐based cognitive Internet of Things networks

Performance analysis of SWIPT‐assisted adaptive NOMA/OMA system with hardware impairments and imperfect CSI

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