Abstract
In this paper, we investigate the cross-layer design of joint channel access and transmission rate adaptation in CR networks with multiple channels for both centralized and decentralized cases. Our target is to maximize the throughput of CR network under transmission power constraint by taking spectrum sensing errors into account. In centralized case, this problem is formulated as a special constrained Markov decision process (CMDP), which can be solved by standard linear programming (LP) method. As the complexity of finding the optimal policy by LP increases exponentially with the size of action space and state space, we further apply action set reduction and state aggregation to reduce the complexity without loss of optimality. Meanwhile, for the convenience of implementation, we also consider the pure policy design and analyze the corresponding characteristics. In decentralized case, where only local information is available and there is no coordination among the CR users, we prove the existence of the constrained Nash equilibrium and obtain the optimal decentralized policy. Finally, in the case that the traffic load parameters of the licensed users are unknown for the CR users, we propose two methods to estimate the parameters for two different cases. Numerical results validate the theoretic analysis.
Highlights
In recent years, the explosive growth of wireless devices and traffic incurs a dramatic increase of the requirement for radio spectrum resource
As today’s spectrum is managed under a fixed assignment policy, which is highly inefficient in terms of spectrum utilization [1, 2], cognitive radios are adopted to sense their environments and promptly reconfigure their communication parameters based on their observations [3,4,5]
At the data link layer, for the transmission capacity analysis, the infinite buffer of the transmitter is assumed to be continually backlogged with packets that must be transmitted to the base station and the channel selection is decided by every CR user
Summary
The explosive growth of wireless devices and traffic incurs a dramatic increase of the requirement for radio spectrum resource. We consider cross-layer design of multichannel access and transmission rate adaptation in CR network for both centralized and decentralized cases by taking the time-varying characteristics of channel state into account. The cross-layer design problem can be modeled by constrained Markov decision process (CMDP) and solved by a dynamic programming method to achieve the optimal performance. Another key difference between our approach and that of the above references is that complexity reduction is explicitly taken into account in our method In both centralized and decentralized cases, the complexity of finding optimal policy increases exponentially with the size of action space and state space, which incurs the so-called curse of dimensionality.
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