Abstract-In this paper we develop a framework for competition of future operators likely to operate in a mixed commons/property-rights regime under the regulation of a spectrum policy server (SPS). The operators dynamically compete for customers as well as portions of available spectrum. The operators are charged by the SPS for the amount of bandwidth they use in their services. Through demand responsive pricing, the operators try to come up with convincing service offers for the customers, while trying to maximize their profits. We first consider a single-user system as an illustrative example. We formulate the competition between the operators as a noncooperative game and propose an SPS-based iterative bidding scheme that results in a Nash equilibrium of the game. Numerical results suggest that, competition increases the user's (customer's) acceptance probability of the offered service, while reducing the profits achieved by the operators. It is also observed that as the cost of unit bandwidth increases relative to the cost of unit infrastructure (fixed cost), the operator with superior technology (higher fixed cost) becomes more competitive. We then extend the framework to a multiuser setting where the operators are competing for a number of users at once. We propose an SPSbased bandwidth allocation scheme in which the SPS optimally allocates bandwidth portions for each user-operator session to maximize its overall expected revenue resulting from the operator payments. Comparison of the performance of this scheme to one in which the bandwidth is equally shared between the useroperator pairs reveals that such an SPS-based scheme improves the user acceptance probabilities and the bandwidth utilization in multiuser systems.
We analyze the effects of pilot assisted channel estimation on achievable data rates (lower bound on information capacity) over a frequency flat time-varying channel. Under a block-fading channel model, the effects of the estimation error are evaluated in the case of the estimates being available at the receiver only (open loop), and in the case when the estimates are fed back to the transmitter allowing water pouring transmitter optimization (closed loop). Using a characterization of the effective noise due to estimation error, we analyze the achievable rates as a function of the power allocated to the pilot, the channel coherence time, the background noise level as well as the number of transmit and receive antennas. The analysis presented here can be used to optimally allocate pilot power for various system and channel operating conditions, and to also determine the effectiveness of closed loop feedback.
In this paper we consider a system where a mobile terminal obtains the downlink channel state information (CSI) and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is AWGN, it can be shown that that unquantized and uncoded (UQ-UC) CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean squared error (MMSE) distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI while incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used in conjunction with the UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of the UQ-UC scheme and also explore the performance in multiple antenna multiuser wireless systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.