Spectral Efficiency of MIMO-NOMA Cognitive Radios with Energy-Based Spectrum Sensing

Yasrab, Tamanna; Gurugopinath, Sanjeev

doi:10.1109/discover47552.2019.9007920

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Therefore, we consider introducing MIMO technology into the CR system to improve its performance. In the literature, most of the research on energy efficiency and user capacity of MIMO-assisted CR networks can be divided into two categories: the traditional CR-MIMO network [25][26][27][28][29][30][31][32][33][34][35] and the network combining CR-MIMO with NOMA (CR-MIMO-NOMA) Technology [36][37][38][39][40][41].…”

Section: Related Workmentioning

confidence: 99%

“…In Reference [40], a new design scheme is proposed to study the problem of coordinated beamforming and power allocation based on interference alignment (IA) in CR-MIMO-NOMA downlink networks. In Reference [41], it is proven that the spectrum efficiency and EE of MIMO-NOMA in the CR network are better than those of an orthogonal multiple access CR network based on MIMO-OMA by using the blindly combined energy detection (BCED).…”

Section: Related Workmentioning

confidence: 99%

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Energy Efficiency and User Capacity Optimization of Cognitive MIMO Systems Via the SCMA-Based Nonorthogonal Time Slot Allocation

Zhang

et al. 2020

Symmetry

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This paper investigates the energy-efficient communications and user capacity in the cognitive multiple input multiple output (MIMO) symmetric system of underlay mode. The advantage of the improved energy efficiency provided by the orthogonal slot allocation for time division multiple access (TDMA) has a side effect of restricting the number of users accessing the system. To tackle the above problem, this paper proposes a nonorthogonal time resource allocation method with sparse code multiple access (SCMA), which allows one to convert the orthogonal slot units of TDMA into non-orthogonal shared slot units for multiple secondary users (SUs). The method of adding virtual users is adopted, wherein each SU is treated as multiple SUs who occupy a shared unit, to facilitate the packet access. Finally, the greedy algorithm is applied to optimize the time slot allocation of unoccupied shared slot units. The simulation results show that SCMA-based nonorthogonal slot allocation can reduce not only the energy consumption by nearly 40%, but also the average power interference from SUs to primary users by nearly 2 dB if their number is relatively high. Moreover, in the case of satisfying the rate requirement of the users, the system user capacity increased by more than 50%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Energy Efficiency and User Capacity Optimization of Cognitive MIMO Systems Via the SCMA-Based Nonorthogonal Time Slot Allocation

Zhang

et al. 2020

Symmetry

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“…5 MIMO-NOMA-CR networks achieve significantly higher throughput than conventional MIMO-CR-based orthogonal multiple access (OMA) networks, which require compulsory spectrum sensing using blind combined energy detection. 6 As CR-NOMA technology can serve more SUs by sharing the licensed spectrum with PUs, it can be considered one of the promising mechanisms to address the requirements of the internet-of-things (IoT) for enormous connections. In addition, energy efficiency has received considerable attention for extending extremely long battery life, particularly for energy-constrained IoT devices.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, CR networks are the face of NOMA, and they are used to increase the quality of service and improve spectrum efficiency 5 . MIMO‐NOMA‐CR networks achieve significantly higher throughput than conventional MIMO‐CR‐based orthogonal multiple access (OMA) networks, which require compulsory spectrum sensing using blind combined energy detection 6 . As CR‐NOMA technology can serve more SUs by sharing the licensed spectrum with PUs, it can be considered one of the promising mechanisms to address the requirements of the internet‐of‐things (IoT) for enormous connections.…”

Section: Introductionmentioning

confidence: 99%

Algorithms and throughput analysis of cognitive radio‐based MIMO‐NOMA for the next generation of wireless communications

Saeed,

Ahmed

2024

Trans Emerging Tel Tech

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In this paper, multi‐users (MU) communications are considered based on the cognitive ratio (CR) technique. Multiple‐input multiple‐output (MIMO) and non‐orthogonal multiple access (NOMA) are proposed to be merged with CR for the sake of improving the achievable throughput and satisfying user fairness. Moreover, utilizing MIMO‐NOMA enables the CR users to be served in the coverage network without the need for spectral sensing. Three scenarios are assumed in this paper to investigate the performance of each CR secondary user (SU) in the presence of single or multiple primary users (PUs). Pairing algorithms are proposed and applied to obtain optimum throughputs and outage probabilities, in which the algorithms are employed to select a PU with an SU to be coupled in a pair, depending on allocating the required power for each user, taking into account that any PU has the priority to reach its required throughput. Moreover, mathematical expressions have been derived for each case to evaluate the required power allocation factor and the achievable throughput for each user. Furthermore, the proposed algorithms show successful and satisfactory achievable rates and outage probabilities.

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“…A variety of current and emerging wireless-related applications make the fifth generation (5G), beyond 5G and Internet-of-Things (IoT) attractive domains, which enable a growing number of physical objects to be connected to the internet with high data rates. [1][2][3][4] Technologies such as WiFi/IEEE 802.11 which are envisioned to be a part of IoT implementation, operate in non-licensed bands and are becoming increasingly congested everyday. [5][6][7] Additionally, it is of utmost importance in an IoT network to ensure that it is capable of handling traffic with numerous wireless nodes connected to the internet.…”

Section: Introductionmentioning

confidence: 99%

Non‐orthogonal multiple access‐aided MIMO cognitive radio networks with selective reporting

Yasrab

Kishore²,

Gurugopinath

2022

Trans Emerging Tel Tech

Self Cite

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In this article, we investigate the performances of conventional cooperative sensing (CCS)‐ and superior selective reporting (SSR)‐based cooperative sensing schemes in a multiple‐input, multiple‐output (MIMO)‐aided non‐orthogonal multiple access (NOMA)‐driven cognitive radio (CR) networks. First, we derive expressions for the probabilities of false‐alarm and signal detection for an optimal detector in the considered MIMO‐NOMA CR setup. Next, we study a constrained optimization problem that maximizes the sum rates of CCS and SSR schemes, with a constraint on the power allocation at SUs. This problem is shown to be a constrained convex optimization problem. Later, we analytically characterize and compare the sum rate performances of CCS and SSR schemes in MIMO‐NOMA CR and MIMO‐based orthogonal multiple access (MIMO‐OMA) CR networks. Extensive computer simulation results are presented which corroborate our analysis, which also quantifies the gain in performance of the proposed MIMO‐NOMA CR network employing SSR scheme when compared to conventional MIMO‐OMA CR systems. Furthermore, we present an experimental study based on RTL‐SDR setup, which supports our theory and also paves way towards a practical implementation of the proposed framework.

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Spectral Efficiency of MIMO-NOMA Cognitive Radios with Energy-Based Spectrum Sensing

Cited by 8 publications

References 10 publications

Energy Efficiency and User Capacity Optimization of Cognitive MIMO Systems Via the SCMA-Based Nonorthogonal Time Slot Allocation

Energy Efficiency and User Capacity Optimization of Cognitive MIMO Systems Via the SCMA-Based Nonorthogonal Time Slot Allocation

Algorithms and throughput analysis of cognitive radio‐based MIMO‐NOMA for the next generation of wireless communications

Non‐orthogonal multiple access‐aided MIMO cognitive radio networks with selective reporting

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