366 research outputs found
Sharing of Unlicensed Spectrum by Strategic Operators
Facing the challenge of meeting ever-increasing demand for wireless data, the
industry is striving to exploit large swaths of spectrum which anyone can use
for free without having to obtain a license. Major standards bodies are
currently considering a proposal to retool and deploy Long Term Evolution (LTE)
technologies in unlicensed bands below 6 GHz. This paper studies the
fundamental questions of whether and how the unlicensed spectrum can be shared
by intrinsically strategic operators without 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 to the standardization and
deployment of LTE in unlicensed bands (LTE-U) are also discussed.Comment: To appear in the IEEE Journal on Selected Areas in Communications,
Special Issue on Game Theory for Network
Worst-Case Robust Distributed Power Allocation in Shared Unlicensed Spectrum
This paper considers non-cooperative and fully-distributed power-allocation
for selfish transmitter-receiver pairs in shared unlicensed spectrum when
normalized-interference to each receiver is uncertain. We model each uncertain
parameter by the sum of its nominal (estimated) value and a bounded additive
error in a convex set, and show that the allocated power always converges to
its equilibrium, called robust Nash equilibrium (RNE). In the case of a bounded
and symmetric uncertainty region, we show that the power allocation problem for
each user is simplified, and can be solved in a distributed manner. We derive
the conditions for RNE's uniqueness and for convergence of the distributed
algorithm; and show that the total throughput (social utility) is less than
that at NE when RNE is unique. We also show that for multiple RNEs, the social
utility may be higher at a RNE as compared to that at the corresponding NE, and
demonstrate that this is caused by users' orthogonal utilization of bandwidth
at RNE. Simulations confirm our analysis
Resource allocation in realistic wireless cognitive radios networks
Cognitive radio networks provide an effective solution for improving spectrum usage for wireless users. In particular, secondary users can now compete with each other to access idle, unused spectrum from licensed primary users in an opportunistic fashion. This is typically done by using cognitive radios to sense the presence of primary users and tuning to unused spectrum bands to boost efficiency. Expectedly, resource allocation is a very crucial concern in such settings, i.e., power and rate control, and various studies have looked at this problem area. However, the existing body of work has mostly considered the interactions between secondary users and has ignored the impact of primary user behaviors. Along these lines, this dissertation addresses this crucial concern and proposes a novel primary-secondary game-theoretic solution which rewards primary users for sharing their spectrum with secondary users. In particular, a key focus is on precisely modeling the performance of realistic channel models with fading. This is of key importance as simple additive white Gaussian noise channels are generally not very realistic and tend to yield overly optimistic results. Hence the proposed solution develops a realistic non-cooperative power control game to optimize transmit power in wireless cognitive radios networks running code division multiple access up-links. This model is then analyzed for fast and slow flat fading channels. Namely, the fading coefficients are modeled using Rayleigh and Rician distributions, and closed-form expressions are derived for the average utility functions. Furthermore, it is also shown that the strategy spaces of the users under realistic conditions must be modified to guarantee the existence of a unique Nash Equilibrium point. Finally, linear pricing is introduced into the average utility functions for both Rayleigh and Rician fast-flat fading channels, i.e., to further improve the proposed models and minimize transmission power for all users. Detailed simulations are then presented to verify the performance of the schemes under the proposed realistic channel models. The results are also compared to those with more basic additive white Gaussian noise channels
Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints
In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels
Competitive Spectrum Management with Incomplete Information
This paper studies an interference interaction (game) between selfish and
independent wireless communication systems in the same frequency band. Each
system (player) has incomplete information about the other player's channel
conditions. A trivial Nash equilibrium point in this game is where players
mutually full spread (FS) their transmit spectrum and interfere with each
other. This point may lead to poor spectrum utilization from a global network
point of view and even for each user individually.
In this paper, we provide a closed form expression for a non pure-FS
epsilon-Nash equilibrium point; i.e., an equilibrium point where players choose
FDM for some channel realizations and FS for the others. We show that operating
in this non pure-FS epsilon-Nash equilibrium point increases each user's
throughput and therefore improves the spectrum utilization, and demonstrate
that this performance gain can be substantial. Finally, important insights are
provided into the behaviour of selfish and rational wireless users as a
function of the channel parameters such as fading probabilities, the
interference-to-signal ratio
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