3,968 research outputs found
Impact of imperfect angle estimation on spatial and directional modulation
In this paper, we investigate the impact of imperfect angle estimation (IAE) on spatial and directional modulation (SDM) systems, assuming that the signal experiences line of sight (LoS) propagation. In SDM systems with IAE, the variation is analyzed in detail, when there is a mismatch between the beamforming and precise channel matrices. Based on the union bound and statistics theory, the average bit error probabilities (ABEPs) for both the legitimate user and eavesdropper are derived. In addition, the ergodic rate is also quantified with IAE. Simulation results are presented to show that the achieved theoretical ABEPs are useful in quantifying the potential performance penalty. We also show that the mismatch between the beamforming and precise channel matrices will become greater with the increase in direction measurement error (DME), which affects the detection for both the legitimate user and eavesdropper. On the other hand, due to the effect of IAE, the SDM requires more signal-to-noise ratio (SNR) gain to achieve a stable ergodic secrecy rate
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities
Recently there has been a flurry of research on the use of reconfigurable
intelligent surfaces (RIS) in wireless networks to create smart radio
environments. In a smart radio environment, surfaces are capable of
manipulating the propagation of incident electromagnetic waves in a
programmable manner to actively alter the channel realization, which turns the
wireless channel into a controllable system block that can be optimized to
improve overall system performance. In this article, we provide a tutorial
overview of reconfigurable intelligent surfaces (RIS) for wireless
communications. We describe the working principles of reconfigurable
intelligent surfaces (RIS) and elaborate on different candidate implementations
using metasurfaces and reflectarrays. We discuss the channel models suitable
for both implementations and examine the feasibility of obtaining accurate
channel estimates. Furthermore, we discuss the aspects that differentiate RIS
optimization from precoding for traditional MIMO arrays highlighting both the
arising challenges and the potential opportunities associated with this
emerging technology. Finally, we present numerical results to illustrate the
power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and
Networking (TCCN
Physical Layer Security in Integrated Sensing and Communication Systems
The development of integrated sensing and communication (ISAC) systems has been spurred by the growing congestion of the wireless spectrum. The ISAC system detects targets and communicates with downlink cellular users simultaneously. Uniquely for such scenarios, radar targets are regarded as potential eavesdroppers which might surveil the information sent from the base station (BS) to communication users (CUs) via the radar probing signal. To address this issue, we propose security solutions for ISAC systems to prevent confidential information from being intercepted by radar targets.
In this thesis, we firstly present a beamformer design algorithm assisted by artificial noise (AN), which aims to minimize the signal-to-noise ratio (SNR) at the target while ensuring the quality of service (QoS) of legitimate receivers. Furthermore, to reduce the power consumed by AN, we apply the directional modulation (DM) approach to exploit constructive interference (CI). In this case, the optimization problem is designed to maximize the SINR of the target reflected echoes with CI constraints for each CU, while constraining the received symbols at the target in the destructive region.
Apart from the separate functionalities of radar and communication systems above, we investigate sensing-aided physical layer security (PLS), where the ISAC BS first emits an omnidirectional waveform to search for and estimate target directions. Then, we formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the Cram\'er-Rao bound (CRB) with the aid of the AN, designing a beampattern with a wide main beam covering all possible angles of targets. The main beam width of the next iteration depends on the optimal CRB. In this way, the sensing and security functionalities provide mutual benefits, resulting in the improvement of mutual performances with every iteration of the optimization, until convergence.
Overall, numerical results show the effectiveness of the ISAC security designs through the deployment of AN-aided secrecy rate maximization and CI techniques. The sensing-assisted PLS scheme offers a new approach for obtaining channel information of eavesdroppers, which is treated as a limitation of conventional PLS studies. This design gains mutual benefits in both single and multi-target scenarios
Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems with Limited Feedback Using ESPAR Antennas
We consider an opportunistic cognitive radio (CR) system consisting of a
primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx),
where SUtx is equipped with an electrically steerable parasitic array radiator
(ESPAR) antenna with the capability of choosing one beam among M beams for
sensing and communication, and there is a limited feedback channel from SUrx to
SUtx. Taking a holistic approach, we develop a framework for integrated
sector-based spectrum sensing and sector-based data communication. Upon sensing
the channel busy, SUtx determines the beam corresponding to PU's orientation.
Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected
beam corresponding to the strongest channel between SUtx and SUrx. We formulate
a constrained optimization problem, where SUtx-SUrx link ergodic capacity is
maximized, subject to average transmit and interference power constraints, and
the optimization variables are sensing duration, thresholds of channel
quantizer at SUrx, and transmit power levels at SUtx. Since this problem is
non-convex we develop a suboptimal computationally efficient iterative
algorithm to find the solution. Our results demonstrate that our CR system
yields a significantly higher capacity, and lower outage and symbol error
probabilities, compared with a CR system that its SUtx has an omni-directional
antenna.Comment: This paper has been submitted to IEEE Transactions on Cognitive
Communications and Networkin
A Light Signalling Approach to Node Grouping for Massive MIMO IoT Networks
Massive MIMO is a promising technology to connect very large numbers of
energy constrained nodes, as it offers both extensive spatial multiplexing and
large array gain. A challenge resides in partitioning the many nodes in groups
that can communicate simultaneously such that the mutual interference is
minimized. We here propose node partitioning strategies that do not require
full channel state information, but rather are based on nodes' respective
directional channel properties. In our considered scenarios, these typically
have a time constant that is far larger than the coherence time of the channel.
We developed both an optimal and an approximation algorithm to partition users
based on directional channel properties, and evaluated them numerically. Our
results show that both algorithms, despite using only these directional channel
properties, achieve similar performance in terms of the minimum
signal-to-interference-plus-noise ratio for any user, compared with a reference
method using full channel knowledge. In particular, we demonstrate that
grouping nodes with related directional properties is to be avoided. We hence
realise a simple partitioning method requiring minimal information to be
collected from the nodes, and where this information typically remains stable
over a long term, thus promoting their autonomy and energy efficiency
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