A Double Auction Framework for Multi-Channel Multi-Winner Heterogeneous Spectrum Allocation in Cognitive Radio Networks

Devi, Monisha; Sarma, Nityananda; Deka, Sanjib Kumar

doi:10.1109/access.2021.3079260

Cited by 13 publications

(10 citation statements)

References 39 publications

(62 reference statements)

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“…Objective Function Optimization Algorithm Auction Auction Mechanism Auction Fairness Spectrum Sensing [8] Maximizing spectrum efficiency Blockchain-based x x x x x x x x x ✓ ✓ ✓ [9] Maximizing spectrum efficiency Heuristic x x x x x x x x x x x x [10] Maximizing allocated spectrum Heuristic x x x x x x ✓ ✓ ✓ x x x [11] Minimizing interference Correlation algorithm x x x x x x x x x ✓ ✓ ✓ [12] Maximizing spectrum efficiency Monte-carlo x x x x x x x x x ✓ ✓ ✓ [13] Maximizing operational power Alternating direction optimization (ADO) x x x x x x x x x ✓ ✓ ✓ [14] Maximizing operational power Numerical simulation x x x x x x x x x ✓ ✓ ✓ [15] Maximizing social welfare (income and fairness) Greedy ✓ ✓ ✓ VCG mechanism ✓ ✓ ✓ x x x [16] Maximizing allocated spectrum Greedy ✓ ✓ ✓ Sealed-bid double auction x x x ✓ ✓ ✓ [17] Maximizing allocated resources (spectrum and antennas) Greedy ✓ ✓ ✓ Clock auction x x x x x x [18] Minimizing costs Greedy ✓ ✓ ✓ Sequential auction x x x ✓ ✓ ✓ [19] Maximizing revenue Greedy ✓ ✓ ✓ Heuristic (flex auction) x x x x x x [20] Maximizing the total utility of the system Greedy ✓ ✓ ✓ Preallocation-based combinatorial auction ✓ ✓ ✓ x x x Our Work…”

Section: Table I: Summary Of the Related Workmentioning

confidence: 99%

“…In [10], a penalty-based fair spectrum allocation algorithm for distributing the available spectrum of incumbent among MNOs is proposed. The author in [16] use a sealed-bid double auction to improve network performance in cognitive radio (CR) technology and network dynamics on the secondary user side. In [22], an approach is employed to derive a function of the minimum average required rate and the antenna price, where the spectrum can be leased in blocks by the virtual network operator (VNO).…”

Section: Table I: Summary Of the Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in 6G Networks

Khadem,

Ansarifard,

Mokari

et al. 2023

Preprint

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Section: Table I: Summary Of the Related Workmentioning

confidence: 99%

Section: Table I: Summary Of the Related Workmentioning

confidence: 99%

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in 6G Networks

Khadem,

Ansarifard,

Mokari

et al. 2023

Preprint

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“…The double auction algorithm for multi-channel multi-winner allocation with heterogeneous channel conditions is proposed in [52]. This algorithm implements the dual auction and allows to collect the bids from the purchaser by an auctioneer and pay off to the seller after completing the transactions.…”

Section: E Double Auction Framework For Multi-channel Multi-winner Al...mentioning

confidence: 99%

Channel Allocation to GAA Users Using Double Deep Recurrent Q-Learning Based on Double Auction Method

Abbass,

Hussain,

Abbas

et al. 2023

IEEE Access

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The SAS-CBRS framework is being tested to share the federally held spectrum with licensed users and opportunistic users to maximize the underutilized spectrum's utility and overcome spectrum scarcity. In the SAS-CBRS framework, radio resources are assigned to the incumbent access (IA), primary access licensees (PAL), and general authorized access (GAA) users according to the given priority. The SAS-CBRS three-tier framework is different from the conventional cognitive radio networks (CRN) as it involves a central entity that acts as a server called a spectrum access system (SAS). The methods to assign the resources using the SAS are still in the research phase. Yet, no standard method is defined by the FCC for resource allocation. The current CRN methods cannot be directly applied because of the addition of the third tier and a central server. Moreover, strict rules are defined for using the 3.5 GHz spectrum band for communication. In this paper, a novel DDRQ-SAS algorithm integrated with the double auction (DA) algorithm is proposed that uses deep recurrent double Q-learning. The DDRQ-SAS is used by the SAS to hold a spectrum auction and create a spectrum pool to get information on PAL channels. PAL operators use the DA algorithm to generate the asking prices intelligently for their available idle channels and the GAA users will use the DA algorithm to intelligently bid for their preferred channels. The DDRQ-SAS-DA algorithm allows the GAA users to get the guaranteed QoS offered by the PAL operators in an auction. GAA users maintain the preference list of the PAL reserved idle channels and bid intelligently based on the available QoS. SAS completes the transaction by allocating the channels to the winning GAAs. The defined problem is also modeled using the double auction multi-winner multi-channel technique and the TDSA-PS algorithm. Numerical results show that the proposed DDRQ-SAS-DA algorithm provides up to 20% better QoS at higher loads for GAA users, generates 24% more revenue for PAL operators, and is 1.6 times more efficient in assigning 500 GAA users.

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“…Hence, this type of access requires extra spectrum sensing by SUs for detecting the idle spectrum of PUs, and SUs are permitted to transmit at the highest power [8]. To solve these issues, a dynamic spectrum sharing and allocation method is developed in CR technology to enhance the efficiency of the spectrum [9], [10]. Then, the SUs select an idle channel for occupying the spectrum and collect the sensing report by the sensing module of the SUs.…”

Section: Introductionmentioning

confidence: 99%

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Pari

Jaisankar

2022

IEEE Access

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Cognitive Radio (CR) is a wireless communication system that is used for intelligent vehicles to solve spectrum scarcity and improve the utilization of the spectrum. However, spectrum sensing and data sharing are difficult due to the presence of malicious nodes which degrades the performance. To overcome these issues, we proposed the BlockCRN-IoCV method which includes authentication, density aware clustering, dual agent based spectrum access and secure beamforming. Here, authentication is performed for both Primary Users (PUs) and Secondary Users (SUs) using the Hybrid Advanced Encryption Standard and Hyper-elliptic Curve Cryptography (AES-HCC) algorithm by considering ID, PUF and location which ensures the legitimacy of the users. To address the mobility of the vehicle we perform density aware clustering using Density aware Dynamic Radius Clustering (DADRC) by considering location, distance and direction for increasing throughput. After completing clustering, we perform efficient spectrum access by using the Dual Agent based Twin Delayed (DA-TD3) algorithm which includes two agents, the first agent performs spectrum sensing by considering SNR, noise level and trust, and the second agent performs spectrum allocation by considering Channel State Information (CSI), in which the CSI is predicted by Quasi-Newton Iterative Unscented Kalman Filter (QNIUKF) algorithm for effective data transmission. Finally, secure beamforming is performed using Bi-Gated Recurrent Neural Network (BiGRU-CapsNet) by considering CSI, beam score, array factor, and direction of angle. The simulation is carried out by OMNET++ and SUMO simulation tools and the performance of this work is evaluated by throughput, packet delivery ratio, SNR, detection accuracy, BER, and delay. The simulation result shows that the proposed work achieves superior performance compared to existing work for secure spectrum sensing and beamforming.

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A Double Auction Framework for Multi-Channel Multi-Winner Heterogeneous Spectrum Allocation in Cognitive Radio Networks

Cited by 13 publications

References 39 publications

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in 6G Networks

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in 6G Networks

Channel Allocation to GAA Users Using Double Deep Recurrent Q-Learning Based on Double Auction Method

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

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