Facing the challenge of meeting ever-increasing demand for wireless data, the industry is striving to exploit large swaths of unlicensed spectrum, which supports open access. Major standards bodies are currently considering a proposal to retool and deploy long term evolution (LTE) technologies in unlicensed bands. This paper studies the fundamental question of how the unlicensed spectrum can be shared by strategic operators to mitigate suffering from the tragedy of the commons. A class of general utility functions is considered. The spectrum sharing problem is formulated as a repeated game over a sequence of time slots. It is first shown that a simple static sharing scheme allows a given set of operators to reach a subgame perfect Nash equilibrium for mutually beneficial sharing. The question of how many operators will choose to enter the market is also addressed by studying an entry game. A sharing scheme, which allows dynamic spectrum borrowing and lending between operators, is then proposed to address time-varying traffic and proved to achieve perfect Bayesian equilibrium. Numerical results show that the proposed dynamic sharing scheme outperforms static sharing, which in turn achieves much higher revenue than uncoordinated full-spectrum sharing. Implications of the results for the standardization and deployment of LTE in unlicensed bands (LTE-U) are also discussed.

Two users at the two ends of a bidirectional channel wish to estimate the common state of the channel. The problem is usually treated as two separate one-way channel estimation problems: User 1 sends deterministic pilots to assist user 2 in estimating the channel, and vice versa. This paper questions whether such separation is optimal. In other words, is it beneficial to let a user choose pilots that adapt to what the user has learned about the channel? Two concrete models are studied and it is found that using adaptive pilots often improves the channel estimate. In the special case of a Gaussian channel with colored additive interference, an iterative bidirectional estimation scheme is proposed, which achieves significantly better performance than separate one-way estimation.