719 research outputs found
Sparse Reconstruction-based Detection of Spatial Dimension Holes in Cognitive Radio Networks
In this paper, we investigate a spectrum sensing algorithm for detecting
spatial dimension holes in Multiple Inputs Multiple Outputs (MIMO)
transmissions for OFDM systems using Compressive Sensing (CS) tools. This
extends the energy detector to allow for detecting transmission opportunities
even if the band is already energy filled. We show that the task described
above is not performed efficiently by regular MIMO decoders (such as MMSE
decoder) due to possible sparsity in the transmit signal. Since CS
reconstruction tools take into account the sparsity order of the signal, they
are more efficient in detecting the activity of the users. Building on
successful activity detection by the CS detector, we show that the use of a
CS-aided MMSE decoders yields better performance rather than using either
CS-based or MMSE decoders separately. Simulations are conducted to verify the
gains from using CS detector for Primary user activity detection and the
performance gain in using CS-aided MMSE decoders for decoding the PU
information for future relaying.Comment: accepted for PIMRC 201
Resource allocation and optimization techniques in wireless relay networks
Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the
useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay
network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The
secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource
allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks
Joint Channel Estimation and Pilot Allocation in Underlay Cognitive MISO Networks
Cognitive radios have been proposed as agile technologies to boost the
spectrum utilization. This paper tackles the problem of channel estimation and
its impact on downlink transmissions in an underlay cognitive radio scenario.
We consider primary and cognitive base stations, each equipped with multiple
antennas and serving multiple users. Primary networks often suffer from the
cognitive interference, which can be mitigated by deploying beamforming at the
cognitive systems to spatially direct the transmissions away from the primary
receivers. The accuracy of the estimated channel state information (CSI) plays
an important role in designing accurate beamformers that can regulate the
amount of interference. However, channel estimate is affected by interference.
Therefore, we propose different channel estimation and pilot allocation
techniques to deal with the channel estimation at the cognitive systems, and to
reduce the impact of contamination at the primary and cognitive systems. In an
effort to tackle the contamination problem in primary and cognitive systems, we
exploit the information embedded in the covariance matrices to successfully
separate the channel estimate from other users' channels in correlated
cognitive single input multiple input (SIMO) channels. A minimum mean square
error (MMSE) framework is proposed by utilizing the second order statistics to
separate the overlapping spatial paths that create the interference. We
validate our algorithms by simulation and compare them to the state of the art
techniques.Comment: 6 pages, 2 figures, invited paper to IWCMC 201
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