Location Dependent Spectrum Pricing of Private LTE and 5G Networks in Europe

Emerging private LTE and 5G services and applications have created need for local radio spectrum licensing. The existing pricing models for licenses do not work well in this context. This paper introduces three new location dependent pricing methods that aim to produce more accurate pricing for local licenses. We use Traficom Frequency Fee as our base-case general spectrum pricing model, and we replace the population density based location coefficient with proxies such as employee density, value added per employee, and rent prices. By comparing the differences in the prices yielded by the models, we show that the new models can in some cases identify high demand areas like hospitals and industrial districts better than the original population density based model. Additionally, we conclude that the original population density based model and the new employee density based model could be used together to capture both the consumer and the industrial spectrum demand simultaneously.

Dynamic Spectrum Pricing with Secondary User’s Normal Demand Preference

During secondary user’s dynamic access to authorized spectrum, a key issue is how to ascertain an appropriate spectrum price so as to maximize primary system’s benefit and satisfy secondary user’s diverse spectrum demands. In this paper, a scheme of pricing-based dynamic spectrum access is proposed. According to the diverse qualities of idle spectrum, the proposed scheme applies a Hotelling game model to form the spectrum pricing problem. Firstly, establish a model of spectrum leasing, among which the idle spectrum with different qualities constitutes a spectrum pool. Then, divide the idle spectrum into equivalent width of leased channels, which will be uniformly sold in order. Secondary users can choose proper channels to purchase in the spectrum pool according to their spectrum usage preferences which are subject to normal distribution and affected by the spectrum quality along with market estimation. This paper analyzes the effect of spectrum pricing according to the primary system’s various tendencies to spectrum usage and economic income. Numerical results evaluate the effectiveness of the proposed pricing method in improving the primary system’s profits.