Spectrum Auction Research Articles

Machine Learning-Powered Combinatorial Clock Auction

We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, several papers have recently proposed machine learning (ML)-based preference elicitation algorithms that aim to elicit only the most important information from bidders. However, from a practical point of view, the main shortcoming of this prior work is that those designs elicit bidders' preferences via value queries (i.e., “What is your value for the bundle {A, B}?''). In most real-world ICA domains, value queries are considered impractical, since they impose an unrealistically high cognitive burden on bidders, which is why they are not used in practice. In this paper, we address this shortcoming by designing an ML-powered combinatorial clock auction that elicits information from the bidders only via demand queries (i.e., “At prices p, what is your most preferred bundle of items?''). We make two key technical contributions: First, we present a novel method for training an ML model on demand queries. Second, based on those trained ML models, we introduce an efficient method for determining the demand query with the highest clearing potential, for which we also provide a theoretical foundation. We experimentally evaluate our ML-based demand query mechanism in several spectrum auction domains and compare it against the most established real-world ICA: the combinatorial clock auction (CCA). Our mechanism significantly outperforms the CCA in terms of efficiency in all domains, it achieves higher efficiency in a significantly reduced number of rounds, and, using linear prices, it exhibits vastly higher clearing potential. Thus, with this paper we bridge the gap between research and practice and propose the first practical ML-powered ICA.

Using quasi-experimental designs for causal effects

Purpose: This paper discusses the concept of identifying the causal effects using quasi-experimental methods and applies this method to investigate the impact of high license fees on the quality of mobile Internet in Poland. Design/methodology/approach: Quasi-experiment design, especially the difference-in-differences method and the interrupted time series design were used to examine the causal effects of spectrum fees in Poland. Data on the quality of mobile Internet in Poland and around the world published by Akamai and data provided by Ookla® under the agreement were used for analysis. Findings: The study did not confirm the impact of high spectrum fees on the quality of the Internet in Poland. Practical implications: The results obtained can help policymakers in Poland and other countries in making decisions on spectrum management. Originality/value: This is the first paper using the quasi-experimental method to examine the effects of the 4G auction in Poland. Keywords: quasi-experiment, difference in difference (DiD), interrupted time series design (ITS), spectrum auction, mobile Internet market. Category of the paper: Research paper.

Estimated Value of Potential Spectrum Auction Receipts in the Next Five-Year Window

Estimated Value of Potential Spectrum Auction Receipts in the Next Five-Year Window

A Toolkit for Spectrum Auctions: Assisting informed and consistent regulatory decision-making

A Toolkit for Spectrum Auctions: Assisting informed and consistent regulatory decision-making

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in UAV-based Networks

Dynamic Fairness-Aware Spectrum Auction for Enhanced Licensed Shared Access in UAV-based Networks

Spectrum Auctions: Designing Markets to Benefit the Public, Industry and the Economy

Evan Kwerel of Federal Communications Commission reviews “Spectrum Auctions: Designing Markets to Benefit the Public, Industry and the Economy” by Geoffrey Myers. The Econlit abstract of this book begins: “Explores challenges of public policy decision-making, providing practical examples of harnessing auctions to elicit information and improve policy decisions.”

Game-Theoretic Specificity of a Competitive Allocation of the Frequency Spectrum

We consider the problem of developing and optimizing the rules of the spectrum auction. One-sided sealed-bid spectrum auctions are studied. Two types of pricing are compared theoretically: the first-price and the second-price. А game model of the auction with free riders is constructed. A free rider uses frequencies purchased by another such participant for free. All Nash equilibria of the obtained games are found and represented in an analytical form. The significant difference between games with all free riders and games with at least one ordinary player is shown. It is proved that when players eliminate their dominated strategies, the resulting auction price of the lot is determined by its value for ordinary players. In the case when all players are free riders, the price is equal to the minimal bid price. The influence of the information the participants have about their partners’ values of a lot on the outcome of the game is discussed. The theoretically obtained properties are in agreement with the results of the experiments presented for spectrum auctions in the scientific literature.

Evaluating the FCC’s $10 Billion Gamble: Successfully Accelerating Access to Spectrum in Auction 107

ABSTRACT This research analyzed how much bidders in the record-breaking C-Band spectrum (3.7–4.2 GHz) auction were willing to pay for earlier access to frequency rights and the policy implications of the incentive system employed by the Federal Communications Commission to clear the band on an accelerated timeline. The analysis found that bidders paid 20.7 percent more on average for licenses available two years earlier with no subsequent legal challenges. Even though it did not follow traditional price discovery, Auction 107 laid the groundwork for accelerating the transition of wide swaths of the spectrum.

A Comparative Study of Auction Theory Applications: Insights from India and Global Perspectives

This research paper presents a comprehensive comparative study of auction theory applications, exploring insights from both the Indian context and global practices. Auction theory plays a vital role in resource allocation, market efficiency, and economic decision-making across various industries. The study analyses different auction mechanisms used in India and other countries, evaluating their effectiveness and suitability in diverse economic environments. The paper delves into specific sectors where auction theory is applied, such as spectrum auctions for telecom operators, infrastructure project auctions, and public procurement auctions for goods and services. By examining auction outcomes, bidder strategies, and their impact on industries, the study provides valuable insights into the adaptation and effectiveness of auction theory in addressing unique challenges and opportunities. The research investigates challenges faced in implementing auction-based systems in India and other economies, offering potential solutions and policy measures to address issues like information asymmetry and regulatory complexities. It compares the economic implications of auction outcomes in India and other countries, including revenue generation and market efficiency. Moreover, the paper explores government initiatives that promote auction-based resource allocation and assesses policy considerations and regulatory frameworks governing auctions in different sectors. Emphasis is placed on the importance of inclusive auction practices in promoting equitable outcomes and fostering financial inclusion. By showcasing international case studies of successful and challenging auctions, the study draws lessons for India's future auction initiatives. The research contributes to the understanding of effective auction-based resource allocation strategies and their potential impact on diverse economic landscapes. In conclusion, this comparative study provides valuable insights into the adaptation, effectiveness, and economic implications of auction theory applications, benefiting policymakers, businesses, and economists seeking to optimize resource allocation and market efficiency. The findings offer valuable guidance for shaping auction mechanisms and promoting fair market practices in both Indian and global contexts. As the study enhances the understanding of auction theory's applications, it contributes to evidence-based decision-making, fostering efficient resource allocation and economic growth.

Bayesian Optimization-Based Combinatorial Assignment

We study the combinatorial assignment domain, which includes combinatorial auctions and course allocation. The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, several papers have recently proposed machine learning-based preference elicitation algorithms that aim to elicit only the most important information from agents. However, the main shortcoming of this prior work is that it does not model a mechanism's uncertainty over values for not yet elicited bundles. In this paper, we address this shortcoming by presenting a Bayesian optimization-based combinatorial assignment (BOCA) mechanism. Our key technical contribution is to integrate a method for capturing model uncertainty into an iterative combinatorial auction mechanism. Concretely, we design a new method for estimating an upper uncertainty bound that can be used to define an acquisition function to determine the next query to the agents. This enables the mechanism to properly explore (and not just exploit) the bundle space during its preference elicitation phase. We run computational experiments in several spectrum auction domains to evaluate BOCA's performance. Our results show that BOCA achieves higher allocative efficiency than state-of-the-art approaches.

The 5G spectrum auction in Chile

In 2021, the Chilean government implemented a first-price package auction to allocate electromagnetic spectrum for 5G mobile services. The auction was run sequentially for different spectrum bands, allowing firms to exploit band complementarities. It was a combinatorial auction, so firms could bid for any combination of blocks within a band. It contemplated spectrum caps – upper limits on the spectrum for each firm – to ensure competitiveness. The beauty contests used in previous processes became obsolete, as there was a need to promote competitiveness and transparency in the telecommunication sector. Four incumbents and one potential entrant participated in the auction. The auction raised more than USD $450 million, which was six times more than the sum of the revenues of all previous contests in the country. We discuss this experience and show how different aspects of the context justified our design choices.

Sealed-bid versus ascending spectrum auctions

We compare the first-price sealed-bid (FPSB) auction and the simultaneous multiple-round auction (SMRA) in an environment based on the recent sale of 900 MHz spectrum in Australia. Three bidders compete for five indivisible items. Bidders can win at most three items and need to obtain at least two to achieve profitable scale, i.e. items are complements. Value complementarities, which are a common feature of spectrum auctions, exacerbate the “fitting problem” and undermine the usual logic for superior price discovery in the SMRA. We find that the FPSB outperforms the SMRA across a range of bidding environments: in terms of efficiency, revenue, and protecting bidders from losses due to the exposure problem. Moreover, the FPSB exhibits superior price discovery and almost always results in competitive (“core”) prices unlike the SMRA, which frequently produces prices that are too low because of demand-reduction or too high because of the exposure problem. We demonstrate the robustness of our findings by considering two-stage variants of the FPSB and SMRA as well as environments in which bidders know their own values but not the distributions from which values are drawn.

Research on the Best Way to Allocate Spectrum Resources: Perspective from Auction

The context of this paper's research is spectrum auctions, and talk in detail about the spectrum auction that took place in the UK in the spring of 2000, as well as other ways of allocating spectrum, comparing them, and classifying the advantages and disadvantages. The reason why this study spectrum auctions is that to compare other methods and choose the best way to allocate spectrum so that both firms and the government can benefit the most. The research method is a case study, by reading the literature and investigating the data, we will analyze the research problem from an objective point of view. Finally, by analyzing several advantages of spectrum auctions, this article find that auctions are indeed the most efficient way to allocate spectrum rather than beauty pageants. The significance of the research is that the allocation of the spectrum can make a large amount of money for the government and at the same time, firms will pay a large amount of money, so the goal of the research in this paper is to find a method that can satisfy both firms and government needs.

PRAM: A Practical Sybil-Proof Auction Mechanism for Dynamic Spectrum Access With Untruthful Attackers

Auction is becoming increasingly popular for dynamic spectrum access (DSA), while it is extremely vulnerable to sybil attacks. Existing studies on sybil-proof DSA auction impractically assume that attackers bid truthfully based on true appraisals. This paper, for the first time, considers untruthful attackers and investigates the sybil-proof auction design in such more hazardous scenarios. To justify the new assumption, we first show that attackers obtain higher utilities by bidding untruthfully, especially in networks with inadequate channels. Based on this novel finding, we then design a practical sybil attack model named EqualSumBid Sybil, where attackers follow an equal-sum rule (i.e., the sum bid value of the multiple identities of an attacker equals the bid value when it bids with only one identity) instead of their true appraisals. To ensure efficient DSA under the new attack, we finally propose the PRAM, a Practical sybil-pRoof Auction Mechanism, where suspicious identity merging and bid-independent bidder sorting methods are introduced to alleviate the effect of untruthfulness on spectrum auction. Furthermore, winner selection and payment methods are designed to resist the EqualSumBid Sybil attack. Theoretical analyses and numerical results show that PRAM not only resists the EqualSumBid Sybil attack but also achieves individual rationality and truthfulness.

Overview of Mobile Communications in Colombia and Introduction to 5G.

The deployment of 5G around the world continues to progress at a rapid pace, especially in North America and Asia. Its advantages and efficiency as a data transmission network have been widely demonstrated in different fields such as agriculture, education, health, and surveillance. However, this process does not have the same dynamics in Latin America, specifically in Colombia. The country is currently implementing actions aimed at facilitating the deployment of this technology in the short term, including pilot tests for the use of the radio spectrum, spectrum auctions, the planning of future auctions, and the review of spectrum caps. The results of this review allow us to conclude that despite the forecasts and the intentions of the Colombian government and mobile communication service operators, 5G in standalone mode will not be commercially available in Colombia before the end of 2023. The main failures in its deployment are related to the lack of available spectrum to support the ultrahigh-reliability and low-latency, enhanced mobile broadband, and massive machine-type communications scenarios, as well as the delay in the auction processes for its assignment.

Learning and Governance in Spectrum Auction Design: Lessons from a Small Island

Learning and Governance in Spectrum Auction Design: Lessons from a Small Island

Reduction of data-value-aware process models: A relevance-based approach

In many settings, verification of process models hinges on data values. A data value is a value in the domain of a data object, e.g., $1000 as the price of a product. Naive exploration of process models with data values, i.e., data-value-aware process models, tends to lead to state-space explosion. To tackle this problem, various reduction techniques have been proposed. These current techniques have a fundamental shortcoming: They do not take the modification of data values by process elements into consideration, in spite of its effects on execution behavior of processes. This may affect the verification result. In this paper, we propose a novel property-specific reduction technique to reduce data-value-aware process models supporting modification of data values. We detect the control-flow nodes and data elements that are necessary to verify a property in question, i.e., elements that are relevant for verification. Then we reduce the data-value-aware process model accordingly. We evaluate our approach by verifying a real-world application: the German 4G spectrum auction model.

A secure double spectrum auction scheme

With the arrival of the 5G era, wireless communication technologies and services are rapidly exhausting the limited spectrum resources. Spectrum auctions came into being, which can effectively utilize spectrum resources. Because of the complexity of the electronic spectrum auction network environment, the security of spectrum auction can not be guaranteed. Most scholars focus on researching the security of the single-sided auctions, while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and buyers. Researchers begin to design the secure double spectrum auction mechanisms, in which two semi-honest agents are introduced to finish the spectrum auction rules. But these two agents may collude with each other or be bribed by buyers and sellers, which may create security risks, therefore, a secure double spectrum auction is proposed in this paper. Unlike traditional secure double spectrum auctions, the spectrum auction server with Software Guard Extensions (SGX) component is used in this paper, which is an Ethereum blockchain platform that performs spectrum auctions. A secure double spectrum protocol is also designed, using SGX technology and cryptographic tools such as Paillier cryptosystem, stealth address technology and one-time ring signatures to well protect the private information of spectrum auctions. In addition, the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification, and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum auctions. Finally, security analysis and performance evaluation of our protocol are discussed.

Proof of Sense: A Novel Consensus Mechanism for Spectrum Misuse Detection

Optimal use of scarce radio spectrum is essential in the proliferation of beyond 5G networks, and promising blockchain technology offers various benefits for the spectrum management. However, existing blockchain-based solutions are expensive, nonoptimized, and lack spectrum fraud detection. This article proposes a novel consensus mechanism for a blockchain-based dynamic spectrum access (DSA) system. The proposed “ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Proof-of-Sense</i> ” consensus mechanism operates based on spectrum sensing procedures rather than cryptographic calculations. It is specially designed to address fraudulent/unauthorized access to the spectrum by analyzing the sensed spectrum data. The core of the consensus mechanism is a cryptographic key sharing mechanism inspired by Shamir’s secret sharing scheme. Moreover, the proposed DSA system can enable different microservices, such as automated spectrum auctions, payment and penalty handling, and spectrum fraud detection. A proof of concept based on experimental approaches coupled with Matlab simulations is presented to analyze the performance of the proposed consensus mechanism.

Economics at the FCC 2021-22: 5G Spectrum Auctions, Affordable Connectivity, Broadband Data Collection, and Merger Review.

The Federal Communications Commission (FCC) is responsible for regulation in the communications marketplace and for management of the nation's non-federal radio spectrum. During the past year, FCC economists continued to work on auctions so as to repurpose mid-band spectrum for advanced wireless services - including 5G - as well as initiatives to close the connectivity gap and make broadband more affordable. FCC economists also evaluated the likely competitive effects of Verizon's proposed acquisition of prepaid competitor TracFone Wireless. Finally, FCC economists helped in setting up the novel Broadband Data Collection.