On Spatial Domain Cognitive Radio Using Single-Radio Parasitic Antenna Arrays

Wilcox, David; Tsakalaki, Elpiniki; Kortun, Ayse; Ratnarajah, Tharmalingam; Papadias, Constantinos B.; Sellathurai, Mathini

doi:10.1109/jsac.2013.130321

Cited by 43 publications

(24 citation statements)

References 24 publications

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“…First, the reactance loads of the parasitic elements are optimized for directivity in a look direction (e.g., 0 ○ ), that can be achieved using a fast iterative beamforming strategy [5], [11]. Then, due to the symmetrical antenna structure, circularly permuting the optimized reactance loads rotate the beampattern to different angular positions, thereby dividing the whole angle space around the ESPAR receiver into several angular sectors.…”

Section: B Projection Matrixmentioning

confidence: 99%

“…In the ESPAR array, analogue beamforming is achieved by tuning reactance values loaded to parasitic elements, which are mutually coupled with the sole active element. Beside the DoA estimation, the ESPAR antenna has also been studied to perform spectrum sensing for cognitive systems [5], [6], and proposed with interference mitigation applications [7].…”

Section: Introductionmentioning

confidence: 99%

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Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction

Qian

Sellathurai

Chambers

2015

2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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In this paper, a direction-of-arrival (DoA) estimation method based on compressive sensing is proposed for an electronically steerable parasitic array radiator (ESPAR) antenna, which uses only a single radio frequency (RF) chain, and is thereby suited for application in compact wireless terminals. Unlike a conventional multi-active antenna array, signals impinging on parasitic elements in an ESPAR array cannot be processed, and only the output of the sole active element can be processed. In this context, for an ESPAR array, a sparse representation of the DoA estimation problem is formulated by first using an overcomplete dictionary composed of samples from the array manifold and then projecting them onto a set of directional beampatterns. The projection matrix is designed to divide the angle space of the receive antenna array into sectors which are accessed via their corresponding sector beampatterns formed on a time division basis. The sparse signal spectrum is reconstructed by the l1-SVD (singular value decomposition) method [1], where the sparsity is enforced by the l1-norm penalty. Simulation results are presented to demonstrate the efficiency of the proposed method.

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Section: B Projection Matrixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction

Qian

Sellathurai

Chambers

2015

2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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“…Assuming there are D primary users transmitting signal in the presence of angular distribution, the received PU signal at the m-th sector can be modeled as [8] …”

Section: System Modelmentioning

confidence: 99%

“…In [8]- [10], the authors consider spatial spectrum sensing with an electronically steerable parasitic array receptor (ESPAR). It divides the angular domain into sectors, which are accessed by beamforming on a time division basis.…”

Section: Introductionmentioning

confidence: 99%

Maximum-minimum spatial spectrum detection for cognitive radio using parasitic antenna arrays

Liu

Jin

2014

2014 IEEE/CIC International Conference on Communications in China (ICCC)

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The spatial spectrum indicates the energy distribution in all directions. If we can get the spatial spectrum, then the spectrum holes in space are known. In spatial spectrum sensing of cognitive radio, an electronically steerable parasitic antenna receptor (ESPAR) divides the space into sectors which are accessed by directional beamforming on a time division basis. Hence, the energy at different direction can be collected respectively, that is, the spatial spectrum is available. In this paper, we first propose a new sensing method using the ratio of maximum-minimum spatial spectrum. Considering the situation of multiple primary users, we then propose an algorithm extension scheme based on the ratio of average-minimum spatial spectrum. The proposed methods can not only overcome the noise uncertainty problem, but also achieve high performance with low complexity. Theoretical performance analysis of the proposed methods is provided. Simulation results based on Nakagami-m fading channel are presented to verify the efficiency of proposed methods.

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“…However, their solution is not very practical, since it assumes the known location information of different nodes, and does not consider the interference, the delay, or the power of each relay node. In [11], the authors use an electronically steerable parasitic antenna receptor to study the spectrum sensing for cognitive radio. They divide the angular domain into sectors, and detect signals from PUs on a time domain.…”

Section: Related Workmentioning

confidence: 99%

Boundary Helps: Efficient Routing Protocol Using Directional Antennas in Cognitive Radio Networks

Dai

2013

2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems

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Abstract-The unpredictable activities of primary users (PUs) make the channel availabilities in cognitive radio networks (CRNs) very unstable. The dynamic channel availabilities cause routing in CRNs to be more difficult than in traditional wireless networks. Specifically, when a source node needs to select a route to reach the destination, the "optimal" route during the route selection phase may not be reliable because of the sudden appearance of a PU, and thus, may not be optimal during the data transmission phase. In this paper, we propose a novel routing protocol based on the source routing in traditional wireless networks. We consider the angle dimension of CRNs by assuming that the directional antennas are equipped on every node. The directional antennas can facilitate the marking of boundary areas of PUs. We use the USRP/Gnuradio to show the sensing result differences of different directions at the boundary area of a primary user. For every optional route between a source node and a destination node, we can evaluate its reliability and other performance by evaluating the PU areas it passes through, and estimating the possible transmission rate of each link on this route. Based on these parameters, we propose an algorithm for route selection, considering both the reliability and delay. Our routing protocol only requires very limited piggyback information, compared to other routing protocols in CRNs. It is efficient and highly adaptable under the dynamic channel availabilities. We evaluate our approach through extensive simulations.

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On Spatial Domain Cognitive Radio Using Single-Radio Parasitic Antenna Arrays

Cited by 43 publications

References 24 publications

Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction

Direction-of-arrival estimation with single-RF ESPAR antennas via sparse signal reconstruction

Maximum-minimum spatial spectrum detection for cognitive radio using parasitic antenna arrays

Boundary Helps: Efficient Routing Protocol Using Directional Antennas in Cognitive Radio Networks

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