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abstract: 'Crowdsourced wireless community network enables individual users to share their private Wi-Fi access points (APs) with each other, hence can achieve a large Wi-Fi coverage with a small deployment cost via crowdsourcing. This paper presents a novel *contract-based* incentive framework to incentivize such a Wi-Fi network crowdsourcing under incomplete information (where each user has certain *private* information such as mobility pattern and Wi-Fi access quality). In the proposed framework, the network operator designs and offers a set of contract items to users, each consisting of a Wi-Fi access price (that a user can charge others for accessing his AP) and a subscription fee (that a user needs to pay the operator for joining the community). Different from the existing contracts in the literature, in our contract model each user’s best choice depends not only on his private information but also on other users’ choices. This greatly complicates the contract design, as the operator needs to analyze the equilibrium choices of all users, rather than the best choice of each single user. We first derive the feasible contract that guarantees the users’ truthful information disclosure based on the equilibrium analysis of user choice, and then derive the optimal (and feasible) contract that yields the maximal profit for the operator. Our analysis shows that a user who provides a higher Wi-Fi access quality is more likely to choose a higher Wi-Fi access price and subscription fee, regardless of the user mobility pattern. Simulation results further show that when increasing the average Wi-Fi access quality of users, the operator can gain more profit, but (counter-intuitively) offer lower Wi-Fi access prices and subscription fees for users.'
author:
- 'Qian Ma,  Lin Gao,  Ya-Feng Liu,  and Jianwei Huang,  [^1] [^2] [^3]'
title: 'Incentivizing Wi-Fi Network Crowdsourcing: A Contract Theoretic Approach'
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Wi-Fi Crowdsourcing, Wireless Community Networks, Incentive Mechanism, Contract Theory.

Conclusion {#sec:conc}
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In this paper, we proposed a novel contract mechanism for crowdsourced wireless community networks under incomplete information. Different from existing contract mechanisms in the literature, the proposed contract considers the coupling among users’ contract item choices, hence is more complicated to design. We analyzed the feasibility and optimality of the proposed contract systematically based on the user equilibrium analysis. We also provided simulation results to illustrate the optimal contract and the profit gain of the operator. Our analysis helps us to understand how different users choose their Wi-Fi sharing schemes, which facilitates the network operator to better optimize her profit in different network and information scenarios. As for the future work, it is important to study a more general model with heterogeneous users, where different users may have different traffic demands and mobility patterns. It is also interesting to study the competition among multiple network operators.

[^1]: This work is supported by the General Research Funds (Project Number CUHK 14206315 and CUHK 14219016) established under the University Grant Committee of the Hong Kong Special Administrative Region, China, and the National Natural Science Foundation of China (Grant Number 61771162, 11631013, and 11688101).

[^2]: Part of this work has been presented at the 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Tempe, Arizona, USA, May 9-13, 2016 [@WiOpt].

[^3]: Qian Ma and Jianwei Huang are with the Department of Information Engineering, The Chinese University of Hong Kong. E-mail: {qianma, jwhuang}@ie.cuhk.edu.hk. Lin Gao (Corresponding Author) is with the School of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen, China. E-mail: gaol@hit.edu.cn. Ya-Feng Liu is with the State Key Laboratory of Scientific and Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China. E-mail: yafliu@lsec.cc.ac.cn.
