Abstract
In this article, we investigate to perform spectrum sensing in two stages for a target long-term evolution (LTE) signal where the main objective is enabling co-existence of LTE femtocells with other LTE femto and macrocells. In the first stage, it is required to perform the sensing as fast as possible and with an acceptable performance under different channel conditions. Toward that end, we first propose sensing the whole LTE signal bandwidth using the fast wavelet transform (FWT) algorithm and compare it to the fast Fourier transform-based algorithm in terms of complexity and performance. Then, we use FWT to go even deeper in the LTE signal band to sense at multiples of a resource block resolution. A new algorithm is proposed that provides an intelligent stopping criterion for the FWT sensing to further reduce its complexity. In the second stage, it is required to perform a finer sensing on the vacant channels to reduce the probability of collision with the primary user. Two algorithms have been proposed for this task; one of them uses the OFDM cyclic prefix for LTE signal detection while the other one uses the primary synchronization signal. The two algorithms were compared in terms of both performance and complexity.
Highlights
Spectrum scarcity has become one of the serious problems facing the wireless communications regulatory bodies especially when the wireless applications and standards are increasing significantly
Two main challenges are associated with the proposed algorithm: 1. The first one is that since the sensing resolution is increased to an resource block (RB) (i.e., 180 kHz), we will need to perform five fast wavelet transform (FWT) stages so the signal is downsampled five times leaving a small number of samples per long-term evolution (LTE) RB to be used for detection
The simulation results have shown that the performance of the intelligent decomposition (ID) algorithm is quite close to the normal algorithm in case of a regular pattern for LTE channel occupancy (i.e., 1 1 0 0 1 1 0 0), which means we achieve the same performance with reduced complexity as shown in Figure in case of an additive white Gaussian noise channels (AWGN) channel and Figure in case of multipath fading channels
Summary
Spectrum scarcity has become one of the serious problems facing the wireless communications regulatory bodies especially when the wireless applications and standards are increasing significantly. The first one is that since the sensing resolution is increased to an RB (i.e., 180 kHz), we will need to perform five FWT stages so the signal is downsampled five times leaving a small number of samples per LTE RB to be used for detection. In this case, it is not necessary to apply wavelet filtering on this section so the complexity is further reduced.
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