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Register a new userA Study of Ultrawideband (UWB) Antenna Design for Cognitive Radio Applications
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Added by
Peshal Nayak
Publication date
2021
fields
Electronic Engineering
and research's language is
English
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Cognitive radio is rapidly shaping the future of wireless communications. Research on antenna design is very critical for the implementation of cognitive radio. A special antenna is required in cognitive radio for sensing and communicating. For the purpose of spectrum sensing, an Ultrawideband (UWB) antenna is being considered as a potential candidate by many experts. This paper provides a detailed discussion of the existing UWB spectrum sensing antenna designs for cognitive radio system. Simulation results for a promising cognitive radio antenna which provides a reconfigurable function in the range of 5-6 GHz have also been presented and shown to match closely with the measured results.
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In this paper we investigate the practical design for the multiple-antenna cognitive radio (CR) networks sharing the geographically used or unused spectrum. We consider a single cell network formed by the primary users (PU), which are half-duplex two-hop relay channels and the secondary users (SU) are single user additive white Gaussian noise channels. In addition, the coexistence constraint which requires PUs coding schemes and rates unchanged with the emergence of SU, should be satisfied. The contribution of this paper are twofold. First, we explicitly design the scheme to pair the SUs to the existing PUs in a single cell network. Second, we jointly design the nonlinear precoder, relay beamformer, and the transmitter and receiver beamformers to minimize the sum mean square error of the SU system. In the first part, we derive an approximate relation between the relay ratio, chordal distance and strengths of the vector channels, and the transmit powers. Based on this relation, we are able to solve the optimal pairing between SUs and PUs efficiently. In the second part, considering the feasibility of implementation, we exploit the Tomlinson-Harashima precoding instead of the dirty paper coding to mitigate the interference at the SU receiver, which is known side information at the SU transmitter. To complete the design, we first approximate the optimization problem as a convex one. Then we propose an iterative algorithm to solve it with CVX. This joint design exploits all the degrees of design. To the best of our knowledge, both the two parts have never been considered in the literature. Numerical results show that the proposed pairing scheme outperforms the greedy and random pairing with low complexity. Numerical results also show that even if all the channel matrices are full rank, under which the simple zero forcing scheme is infeasible, the proposed scheme can still work well.
A novel and compact dual band planar antenna for 2.4/5.2/5.8-GHz wireless local area network(WLAN) applications is proposed and studied in this paper. The antenna comprises of a T-shaped and a F-shaped element to generate two resonant modes for dual band operation. The two elements can independently control the operating frequencies of the two excited resonant modes. The T-element which is fed directly by a 50 $Omega$ microstrip line generates a frequency band at around 5.2 GHz and the antenna parameters can be adjusted to generate a frequency band at 5.8 GHz as well, thus covering the two higher bands of WLAN systems individually. By couple-feeding the F-element through the T-element, a frequency band can be generated at 2.4 GHz to cover the lower band of WLAN system. Hence, the two elements together are very compact with a total area of only 11$times$6.5 mm$^{2}$. A thorough parametric study of key dimensions in the design has been performed and the results obtained have been used to present a generalized design approach. Plots of the return loss and radiation pattern have been given and discussed in detail to show that the design is a very promising candidate for WLAN applications.
MIMO transmit arrays allow for flexible design of the transmit beampattern. However, the large number of elements required to achieve certain performance using uniform linear arrays (ULA) maybe be too costly. This motivated the need for thinned arrays by appropriately selecting a small number of elements so that the full array beampattern is preserved. In this paper, we propose Learn-to-Select (L2S), a novel machine learning model for selecting antennas from a dense ULA employing a combination of multiple Softmax layers constrained by an orthogonalization criterion. The proposed approach can be efficiently scaled for larger problems as it avoids the combinatorial explosion of the selection problem. It also offers a flexible array design framework as the selection problem can be easily formulated for any metric.
While on the one hand 5G and B5G networks are challenged by ultra-high data rates in wideband applications like 100+ Gbps wireless Internet access, on the other hand they are expected to support reliable low-latency Internet of Things (IoT) applications with ultra-high connectivity. These conflicting challenges are addressed in a system proposal dealing with both extremes. In contrast to most recent publications, focus is on the frequency domain below 10~GHz. Towards this goal, multi-mode antenna technology is used and different realizations, offering up to eight uncorrelated ports per radiator element, are studied. Possible baseband architectures tailored to multi-mode antennas are discussed, enabling different options regarding precoding and beamforming.
Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users. Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple primary user receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that the introduction of IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.
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