Optimal Joint Partitioning and Licensing of Spectrum Bands in Tiered Spectrum Access under Stochastic Market Models

We consider the problem of partitioning an entire band into M channels of equal bandwidth, and then further assigning these M channels into $P\leq M$ licensed channels and M–P unlicensed channels. Licensed channels can be accessed both for licensed use and opportunistic use while unlicensed channels can be accessed only for opportunistic use. The access to licensed channels follows a tiered structure, where licensed use has a higher priority than opportunistic use. We address the following question in this paper. Given a market setup, what values of M and P maximize the net spectrum utilization of the entire bandwidth? This abstract problem is highly relevant in practical scenarios, e.g., in the context of partitioning the recently proposed Citizens Broadband Radio Service band. If M is too high (low), it may decrease (increase) spectrum utilization due to limited (wastage of) channel capacity. If P is too high (low), it will not incentivize the wireless operators who are primarily interested in licensed (unlicensed) channels to join the market. These trade-offs are captured in the optimization problem which is modeled as a two-stage Stackelberg game consisting of the regulator and the wireless operators. We design an algorithm to solve the Stackelberg game in order to find the optimal M and P. We use this algorithm to obtain interesting numerical results that suggest how the optimal values of M and P change with different market settings.

[1]  Dusit Niyato,et al.  Pricing, Spectrum Sharing, and Service Selection in Two-Tier Small Cell Networks: A Hierarchical Dynamic Game Approach , 2014, IEEE Transactions on Mobile Computing.

[2]  Randall Berry,et al.  Competition with Three-Tier Spectrum Access and Spectrum Monitoring , 2019, MobiHoc.

[3]  Yanjiao Chen,et al.  Balancing Income and User Utility in Spectrum Allocation , 2015, IEEE Transactions on Mobile Computing.

[4]  Jeffrey G. Andrews,et al.  Optimal spectrum partition and mode selection in device-to-device overlaid cellular networks , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[5]  Anirudha Sahoo Fair resource allocation in the citizens broadband radio service band , 2017, 2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[6]  I. Gilboa Theory Of Decision Under Uncertainty , 2009 .

[7]  Y. Tohidi,et al.  Sequential Coordination of Transmission Expansion Planning With Strategic Generation Investments , 2017, IEEE Transactions on Power Systems.

[8]  Bo Li,et al.  HEAD: A hybrid spectrum trading framework for QoS-aware secondary users , 2014, 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN).

[9]  Coleman Bazelon Licensed or unlicensed: The economic considerations in incremental spectrum allocations , 2008, IEEE Communications Magazine.

[10]  Michael L. Honig,et al.  Competitive Resource Allocation in HetNets: The Impact of Small-Cell Spectrum Constraints and Investment Costs , 2017, IEEE Transactions on Cognitive Communications and Networking.

[11]  Qingkai Liang,et al.  Robust design of spectrum-sharing networks , 2016, 2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[12]  Jeffrey G. Andrews,et al.  Bandwidth partitioning in decentralized wireless networks , 2007, IEEE Transactions on Wireless Communications.

[13]  Qian Zhang,et al.  FlexAuc: Serving Dynamic Demands in a Spectrum Trading Market With Flexible Auction , 2014, IEEE Transactions on Wireless Communications.

[14]  Michael L. Honig,et al.  Sequential Bandwidth and Power Auctions for Distributed Spectrum Sharing , 2008, IEEE Journal on Selected Areas in Communications.