Network Utility Maximization Based on an Incentive Mechanism for Truthful Reporting of Local Information

Gao, Jie; Zhao, Lian; Shen, Xuemin

doi:10.1109/tvt.2018.2825278

Cited by 38 publications

(17 citation statements)

References 43 publications

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“…where the SINR values γ t−1 and estimated transmission power p t−1 in the previous iteration are used to have a constant value in the right-hand side of (18), andM l,i (•) in (39) is derived in the Appendix. With this simplification, the equations in (18) are decoupled and their solutions can be easily reached by a numerical algorithm by a network central unit. To estimate the transmission power in the t − 1 iteration p t−1 , an average over the time index t − 1 is considered:…”

Section: B Utility Optimizationmentioning

confidence: 99%

Distributed Utility Optimization in Vehicular Communication Systems

Diaz-Ibarra

Campos-Delgado

Gutiérrez

et al. 2020

IEEE Trans. Veh. Technol.

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In this paper, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network. Index Terms-Vehicular communications, transmission power, utility maximization, feedback control. I. INTRODUCTION A. Motivation V EHICULAR communication networks (VCN) are an emerging technology aimed at improving road safety and traffic management [1]-[3]. These networks will enable vehicles to share their driving information with other vehicles, and also with the infrastructure installed along the road in real-time. Two types of messages will be employed to transmit (broadcast) such Manuscript

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Section: B Utility Optimizationmentioning

confidence: 99%

Distributed Utility Optimization in Vehicular Communication Systems

Diaz-Ibarra

Campos-Delgado

Gutiérrez

et al. 2020

IEEE Trans. Veh. Technol.

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“…where d n,k = 1 − e −x n,k , and λ n,k is regarded as a penalty price to prevent devices from always trying to access the channel and causing a heavy collision [31]. To this end, we give Lemma 1 and Lemma 2, to prove the existence and uniqueness of NE of the new game G = N , {x n } n∈N , {U n } n∈N .…”

Section: Barring Policy Under Qos Guarantee a Distributed Game-tmentioning

confidence: 99%

Game-Theoretic Optimization for Machine-Type Communications Under QoS Guarantee

Gü

Cui

et al. 2019

IEEE Internet Things J.

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Massive machine-type communication (mMTC) is a new focus of services in fifth generation (5G) communication networks. The associated stringent delay requirement of endto-end (E2E) service deliveries poses technical challenges. In this paper, we propose a joint random access and data transmission protocol for mMTC to guarantee E2E service quality of different traffic types. First, we develop a priority-queueingbased access class barring (ACB) model and a novel effective capacity is derived. Then, we model the priority-queueingbased ACB policy as a non-cooperative game, where utility is defined as the difference between effective capacity and access penalty price. We prove the existence and uniqueness of Nash equilibrium (NE) of the non-cooperative game, which is also a sub-modular utility maximization problem and can be solved by a greedy updating algorithm with convergence to the unique NE. To further improve the efficiency, we present a price-update algorithm, which converges to a local optimum. Simulations demonstrate the performance of the derived effective capacity and the effectiveness of the proposed algorithms. IndexTerms-Massive machine-type communications (mMTC), random access, effective capacity, quality of service (QoS), non-cooperative game, sub-modular function.

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“…A maximum matching is found to obtain an efficient relay assignment. Auctions for D2D networks are also studied in [12]. An auction mechanism to induce truthful reporting of private local information in a D2D network scenario is proposed in [12].…”

Section: Related Workmentioning

confidence: 99%

Beyond the VCG Mechanism: Truthful Reverse Auctions for Relay Selection with High Data Rates, High Base Station Utility and Low Interference in D2D Networks

MVS¹,

Pancholi²,

Priyanka³

et al. 2019

Preprint

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Device-to-Device communication allows a cellular user (relay node) to relay data between the base station (BS) and another cellular user (destination node). We address the problem of designing reverse auctions to assign a relay node to each destination node, when there are multiple potential relay nodes and multiple destination nodes, in the scenarios where the transmission powers of the relay nodes are: 1) fixed, 2) selected to achieve the data rates desired by destination nodes, and 3) selected so as to approximately maximize the BS's utility. We show that auctions based on the widely used Vickrey-Clarke-Groves (VCG) mechanism have several limitations in scenarios 1) and 2); also, in scenario 3), the VCG mechanism is not applicable. Hence, we propose novel reverse auctions for relay selection in each of the above three scenarios. We prove that all the proposed reverse auctions can be truthfully implemented as well as satisfy the individual rationality property. Using numerical computations, we show that in scenarios 1) and 2), our proposed auctions significantly outperform the auctions based on the VCG mechanism in terms of the data rates achieved by destination nodes, utility of the BS and/ or the interference cost incurred to the BS.

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Network Utility Maximization Based on an Incentive Mechanism for Truthful Reporting of Local Information

Cited by 38 publications

References 43 publications

Distributed Utility Optimization in Vehicular Communication Systems

Distributed Utility Optimization in Vehicular Communication Systems

Game-Theoretic Optimization for Machine-Type Communications Under QoS Guarantee

Beyond the VCG Mechanism: Truthful Reverse Auctions for Relay Selection with High Data Rates, High Base Station Utility and Low Interference in D2D Networks

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