# Multi-channel Sensing And Resource Allocation in Energy Constrained Cognitive Radio Networks

## TL;DR

This paper addresses energy-efficient sensing and resource allocation in multi-channel cognitive radio networks, optimizing throughput while respecting primary user QoS and energy constraints.

## Contribution

It introduces a novel resource allocation framework for energy-constrained secondary users in multi-channel cognitive radio networks, considering sensing time, transmission power, and multiple users.

## Key findings

- Optimal sensing and transmission strategies improve throughput.
- Energy constraints significantly impact sensing and transmission decisions.
- Channel occupancy and fading affect the performance of the proposed method.

## Abstract

We consider a cognitive radio network in a multi-channel licensed environment. Secondary user transmits in a channel if the channel is sensed to be vacant. This results in a tradeoff between sensing time and transmission time. When secondary users are energy constrained, energy available for transmission is less if more energy is used in sensing. This gives rise to an energy tradeoff. For multiple primary channels, secondary users must decide appropriate sensing time and transmission power in each channel to maximize average aggregate-bit throughput in each frame duration while ensuring quality-of-service of primary users. Considering time and energy as limited resources, we formulate this problem as a resource allocation problem. Initially a single secondary user scenario is considered and solution is obtained using decomposition and alternating optimization techniques. Later we extend the analysis for the case of multiple secondary users. Simulation results are presented to study effect of channel occupancy, fading and energy availability on performance of proposed method.