101 research outputs found
Cooperative secure transmission relying on the optimal power allocation in the presence of untrusted relays, a passive eavesdropper and hardware impairments
No full textIn this work, by considering a variety of realistic hardware impairments, we aim to enhance the security of a cooperative relaying network, where a source intends to transmit its confidential information to a destination in the presence of a group of untrusted amplify-and-forward relays, as potential eavesdroppers (Eves), and an entirely passive multiple-antenna aided Eve. Our goal is to safeguard the information against these two types of eavesdropping attacks, while simultaneously relying on the untrusted relays to boost both the security and reliability of the network. To reach this goal, we propose a novel joint cooperative beamforming, jamming and power allocation policy to safeguard the confidential information while concurrently achieving the required quality-of-service at the destination. We also take into account both the total power budget constraint and a practical individual power constraint for each node. Our optimization problem can be split into two consecutive sub-problems. In the first sub-problem, we are faced with a non-convex problem which can be transformed into the powerful difference of convex (DC) program. A low-complexity iterative algorithm is proposed to solve the DC program, which relies on the constrained concave-convex procedure (CCCP). We further introduce a novel initialization method, which is based on a feasible point of the original problem obtained from a novel iterative feasibility search procedure, rather than an arbitrary (infeasible) point as in the conventional CCCP. The second sub-problem of our optimization problem is a convex optimization problem and can be solved efficiently adopting the classic interior point method. The numerical results provided illustrate that although the trusted relaying scenario outperforms the untrusted relaying for small and medium total power budgets, however, by increasing the total power budget, the secrecy performances of both the trusted and untrusted relaying converge to the same. Additionally, by equally sharing the total impairments at the relays between the transmitter and the receiver the best secrecy performance is presented
Maximizing the secrecy energy efficiency of the cooperative rate-splitting aided downlink in multi-carrier UAV networks
No full textAlthough Unmanned Aerial Vehicles (UAVs) are capable of significantly improving the information security by detecting the eavesdropper's location, their limited energy motivates our research to propose a secure and energy efficient scheme. Thanks to the common-message philosophy introduced by Rate-Splitting (RS), we no longer have to allocate a portion of the transmit power to radiate Artificial Noise (AN), and yet both the Energy Efficiency (EE) and secrecy can be improved. Hence we define and study the Secrecy Energy Efficiency (SEE) of a multi-carrier multi-UAV network, in which Cooperative Rate-Splitting (CRS) is employed by each multi-antenna UAV Base-Station (UAV-BS) for protecting their downlink transmissions against an external eavesdropper (Eve). Furthermore, we consider the challenging scenario in which CRS is employed by each multi-antenna UAV-BS to protect their corresponding downlink transmissions against an external Eve. We further consider a difficult scenario in terms of security in which only imperfect channel state information of Eve is available at the Tx. Accordingly, we conceive a robust secure resource allocation algorithm, which maximizes the SEE by jointly optimizing both the user association matrix and the network parameter allocation problem, including the RS precoders, time slot sharing and power allocation. Due to the non-convexity of the problem, it is decoupled into a pair of convex sub-problems. Firstly, new two-tier intra-cell optimization problems are formulated for achieving ξ-optimal solutions by iterative block coordinate decent programming. Then, the power of each sub-channel is optimized by formulating the associated power control problem. Simulation results confirm that the scheme conceived enhances both the secrecy and energy efficiency of the system compared to the existing cooperative non-orthogonal benchmarks
Large-scale rate-splitting multiple access in uplink UAV networks: effective secrecy throughput maximization under limited feedback channel
No full textUnmanned aerial vehicles (UAVs) are capable of improving the performance of next generation wireless systems. However, their communication performance is prone to both channel estimation errors and potential eavesdropping. Hence, we investigate the effective network secrecy throughput (ENST) of the uplink UAV network, in which rate-splitting multiple access (RSMA) is employed by each legitimate user for secure transmission under the scenario of massive access. To maximize the ENST, the transmission rate versus power allocation relationship is formulated as a max-min optimization problem, relying on realistic imperfect channel state information (CSI) of both the legitimate users and passive eavesdroppers (Eves). In the model considered, each user transmits a superposition of two messages to a UAV base-stations (UAV-BS), each having different transmit power and the UAV-BS adopts a successive interference cancellation (SIC) technique to decode the received messages. Given the non-convexity of the problem, it is decoupled into a pair of sub-problems. In particular, we derive a closed form expression for the optimal rate-splitting fraction of each user. Then, given the optimal rate-splitting fraction of each user, the \epsilon-constrainted transmit power of each user is calculated by harnessing sequential parametric convex approximation (SPCA) programming. Our simulation results confirm that the scheme conceived significantly improves the ENST compared to both the existing orthogonal and non-orthogonal benchmarks.</p
On the physical layer security of the cooperative rate-splitting aided downlink in UAV networks
No full textUnmanned Aerial Vehicles (UAVs) have found compelling applications in intelligent logistics, search and rescue as well as in air-borne Base Station (BS). However, their communications are prone to both channel errors and eavesdropping. Hence, we investigate the max-min secrecy fairness of UAV-aided cellular networks, in which Cooperative Rate-Splitting (CRS) aided downlink transmissions are employed by each multi-antenna UAV Base Station (UAV-BS) to safeguard the downlink of a two-user Multi-Input Single-Output (MISO) system against an external multi-antenna Eavesdropper ( Eve ). Realistically, only Imperfect Channel State Information (ICSI) is assumed to be available at the transmitter. Additionally, we consider a realistic total power constraint and guarantee the specific Quality of Service (QoS) requirements of the legitimate users. To handle the worst-case channel uncertainty of the legitimate users and an external Eve , we conceive a robust secure resource allocation algorithm, which maximizes the minimum worst-case secrecy rate of the legitimate users. Based on the CRS principle, the transmitter splits and encodes the messages of legitimate users into common as well as private streams and the user having stronger CSI is asked to help the cell-edge user by opportunistically forwarding its decoded common message. In contrast to the existing schemes adopted in the literature for ensuring secure transmission of the first cooperative phase only, in our proposed solution the common message has a twin-fold mission. Explicitly, apart from serving as the desired message, it also acts as Artificial Noise (AN) for drowning out Eve without consuming extra power. This is in stark contrast to the conventional AN designs. In the second phase, the pure AN is directed towards the Eve , deploying a robust Maximum Ratio Transmitter (MRT) beamformer at the UAV-BS. To solve the resultant non-convex optimization problem we resort to the Sequential Parametric Convex Approximation (SPCA) method together with a bespoke initialization algorithm to avoid any failure due to infeasibility. Our simulation results confirm that the proposed secure transmission scheme outperforms the existing cooperative benchmarkers.</p
Antenna and pulse selection for colocated MIMO radar
No full textMultiple input multiple output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. However, the increased hardware cost (due to multiple transmitters and receivers), power consumption (due to multiple transmitters and pulses), and computational complexity (due to numerous pulses) form the drawbacks of MIMO radar. On one hand, a higher estimation accuracy is required, but on the other hand, a lower number of active antennas/pulses is desirable. Therefore, in this paper, by proposing a convex optimization approach for the general case of transmitter-receiver-pulse selection, we will minimize the total number of active antennas/pulses in order to guarantee a prescribed performance accuracy. The performance measure we will optimize is the Cramer-Rao lower bound (CRLB) for the angle and velocity estimation accuracy of two targets, which provides a trade-off between the main beamwidth and the sidelobe level (SLL) of the ambiguity function.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Signal Processing System
Rate-distortion regions for successively structured multiterminal source coding schemes
No full textMultiterminal source coding refers to separate encoding and joint decoding of multiple correlated sources. Joint decoding requires all the messages to be decoded simultaneously which is exponentially more complex than a sequence of single-message decodings. Inspired by previous work on successive coding strategy, which is based on successive decoding structure, we apply the successive Wyner-Ziv coding to different schemes of multiterminal source coding problem. We address the problem from an information theoretic perspective and determine the rate region for three different multiterminal coding schemes: Gaussian CEO problem, 1-helper problem, and 2-terminal source coding problem. We prove that the optimal sum-rate distortion performance for the CEO problem is achievable using the successive coding strategy which is essentially a low complexity approach for obtaining a prescribed distortion. We show that if the sum-rate tends to infinity for a finite number of agents (sensors), the optimal rate allocation strategy assigns equal rates to all agents. The same result is obtained when the number of agents tends to infinity while the sum-rate is finite. Then, we consider 1-helper source coding scheme where one source provides partial side information to the decoder to help the reconstruction of the other source. Our results show that the successive coding strategy is an optimal strategy in this scheme in the sense of achieving the rate-distortion function. For the 2-terminal source coding problem, we develop connections between source encoding and data fusion steps and prove that the whole rate-distortion region is achievable using the successive coding strategy. Comparing the performance of the sequential coding with the performance of the successive coding, we show that there is no sum-rate loss when the side information is not available at the encoder. This result is of special interest in some applications such as video coding where there are processing and storage constraints at the encoder. Based on the successive coding strategy, we provide an achievable rate-distortion region for the m-terminal source coding. We also consider a distributed network, modeled by CEO problem with Gaussian multiple access channel (MAC), where L noisy observations of a memoryless Gaussian source are transmitted through an additive white Gaussian MAC to a decoder. The decoder wishes to reconstruct the main source with an average distortion D at the smallest possible power consumption in the communication link. Our goal is to characterize the power-distortion region achievable by any coding strategy regardless of delay and complexity. We obtain a necessary condition for achievability of all power-distortion tuples ( P 1 , P 2 ,..., P L , D ). Also, analyzing the uncoded transmission scheme provides a sufficient condition for achievability of ( P 1 , P 2 ,..., P L , D ). Then, we consider a symmetric case of the problem where the observations of agents have the same noise level and the transmitting signals are subject to the same average power constraint. We show that in this case the necessary and sufficient conditions coincide and give the optimal power-distortion region. Therefore, in the symmetric case of Gaussian CEO problem uncoded transmission over a Gaussian MAC performs optimally for any finite number of agent
On the transmission of a Gaussian source over an AWGN channel with correlated interference
No full textOptimal HDA codes for sending a Gaussian source over a Gaussian channel with bandwidth compression in the presence of an interference
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