Power Control in Cognitive Radio Networks Using Cooperative Modulation and Coding Classification

In this paper, a centralized Power Control (PC)
scheme aided by interference channel gain learning is proposed
to allow a Cognitive Radio (CR) network to access the frequency
band of a Primary User (PU) operating based on an Adaptive
Coding and Modulation (ACM) protocol. The main idea is the
CR network to constantly probe the band of the PU with
intelligently designed aggregated interference and sense whether
the Modulation and Coding scheme (MCS) of the PU changes in
order to learn the interference channel gains. The coordinated
probing is engineered by the Cognitive Base Station (CBS),
which assigns appropriate CR power levels in a binary search
way. Subsequently, each CR applies a Modulation and Coding
Classification (MCC) technique and sends the sensing information
through a control channel to the CBS, where all the MCC
information is combined using a fusion rule to acquire an MCS
estimate of higher accuracy and monitor the probing impact to
the PU MCS. After learning the normalized interference channel
gains towards the PU, the CBS selects the CR power levels to
maximize total CR network throughput while preserving the
PU MCS and thus its QoS. The effectiveness of the proposed
technique is demonstrated through numerical simulations.