We consider private commons for secondary sharing of licensed spectrum bands with no access coordination provided by the primary license holder. In such environments, heterogeneity in demand patterns of the secondary users can lead to constant changes in the interference levels, and thus can be a source of volatility to the utilities of the users. In this paper, we consider secondary users to be service providers that provide downlink services. We formulate the spectrum sharing problem as a non-cooperative iterated game of power control where service providers change their power levels to fix their long-term average rates at utility-maximizing values. First, we show that in any iterated 2x 2 game, the structure of the single-stage game dictates the degree of control that a service provider can exert on the long-term outcome of the game. Then we show that if service providers use binary actions either to access or not to access the channel at any round of the game, then the long-term rate can be fixed regardless of the strategy of the opponent. We identify these rates and show that they can be achieved using mixed Markovian strategies which will be also identified.

We investigate profitability from secondary spectrum provision under unknown relationships between price charged for spectrum use and demand drawn at the given price. We show that profitability is governed by the applied admission policy and the price charged to secondary users. We explicitly identify a critical price (market entry price) such that if secondary demand is charged below that price, the licensee endures losses from spectrum provision, regardless of the applied admission policy. Furthermore, we show that an admission policy that admits secondary demand only when no channel is occupied is profitable for any price that exceeds the critical price. We prove that this policy is profit-robust to variations in secondary demand, i.e., if the policy is profitable for a certain price, it will be profitable for any secondary demand that the price generates, as long as the price generates demand. We also investigate profitability from a set of policies that allow more secondary users to access spectrum by defining the number of users that can be concurrently served. Our results demonstrate profit-robustness of these policies and explicitly characterize profitable prices. We provide a numerical study to verify our theoretical findings.

We study the engineering of heterogeneous cellular networks composed of a macrocell and some picocells by investigating the interplay of different network processes and parameters such as channel allocation, user association and reuse pattern (to control inter-cell interference between picocells). We formulate a joint association, channel allocation, and inter-cell interference management problem that relies on very few assumptions. This problem turns out to be an Integer Non-Linear program that is NP-hard. However, its structure is such that we can solve it exactly for relatively large size systems. We use optimal solutions as benchmarks to understand how different simple association schemes perform. Our results show the critical impact of the association rules on system performance and shows the interplay of the different processes and parameters. We believe that these insights will help design online association schemes in the future.

We consider pricing secondary access to wireless spectrum in cellular CDMA networks. We study the case for a primary license holder interested in leasing the right of providing service in a given geographical region of its coverage network. The goal is to price access to the cells in that region under heterogeneous call traffic demand with the objective of profit maximization. While a revenue is gained from the leased region due to the exercised price, the primary license holder incurs a loss due to reduced spatial coverage of the network and also due to interference effect from the leased into the retained region. We exploit the spatial effect of interference due to geographical locations of the cells and set a price per cell rather than pricing the whole region by a scalar quantity. We employ reduced load approximations which have proved useful in classical telephony and characterize optimal prices for different pricing philosophies, e.g., flat pricing and demand-based pricing. The obtained formula of prices suggests charging per admitted call in proportion with the interference that the call generates. The charged amount balances the corresponding loss of revenue due to the influence of an admitted call. We present an iterative price computing technique and provide a numerical study in support of our analytical results.

We consider feed-forward packet switched networks with fixed routing and random congestion losses. Users of the network are assumed to be greedy in the sense that each user increases its traffic rate in proportion to profit per packet that it generates. Using a deterministic fluid model, we propose perpacket pricing policies to control packet generation rates of users. The resulting rates are shown to stabilize at local maxima of two suitable choices of social welfare in the network. We give decentralized algorithms for network links to compute their prices in a stateless fashion based on piggybacking control messages on acknowledgements. The obtained analytical conclusions are verified via packet-level simulations.