arXiv subjects

Vahid Tabataba Vakili

Publications and source records attributed to Vahid Tabataba Vakili.

8 recordsLinked to original sources

arXiv2022

Active User Detection and Channel Estimation for Spatial-based Random Access in Crowded Massive MIMO Systems via Blind Super-resolution

This work presents a novel framework for random access in crowded scenarios of multiple-input multiple-output(MIMO) systems. A multi-antenna base station (BS) and multiple single-antenna users are considered in these systems. A huge portion of the system resources is dedicated as orthogonal pilots for accurate channel estimation which imposes a huge training overhead. This overhead can be highly mitigated by exploiting intrinsic angular domain sparsity of massive MIMO channels and the sporadic traffic of users, i.e., few number of users are active to sent or receive data in each coherence interval. In fact, the angles of arrivals (AoAs) coming from active users are continuous parameters and can take any arbitrary values. Besides, the AoAs corresponding to each active user are alongside each other forming a specific cluster. This work revolves around exploiting these features. Specifically, a blind clustering-based algorithm is proposed that not only recovers the transmitted data by users in grant free random access and primary pilots in random access blocks of coherent transmission, but also provides accurate channel estimation. Our approach is based on transforming the unknown variables into a higher dimensional space with matrix variables. An off-grid atomic norm minimization is then proposed to obtain the unknown matrix from only a few observed arrays at the BS. Then, a clustering-based approach is employed to identify which AoAs correspond to which active users. After identifying active users and their AoAs, an alternating-based approach is performed to obtain the channels and data or primary pilots of active users. Simulation results demonstrate the effectiveness of our approach in AoA detection as well as data recovery.

cs.IT↗

arXiv2020

An Autonomous Intrusion Detection System Using an Ensemble of Advanced Learners

An intrusion detection system (IDS) is a vital security component of modern computer networks. With the increasing amount of sensitive services that use computer network-based infrastructures, IDSs need to be more intelligent and autonomous. Aside from autonomy, another important feature for an IDS is its ability to detect zero-day attacks. To address these issues, in this paper, we propose an IDS which reduces the amount of manual interaction and needed expert knowledge and is able to yield acceptable performance under zero-day attacks. Our approach is to use three learning techniques in parallel: gated recurrent unit (GRU), convolutional neural network as deep techniques and random forest as an ensemble technique. These systems are trained in parallel and the results are combined under two logics: majority vote and "OR" logic. We use the NSL-KDD dataset to verify the proficiency of our proposed system. Simulation results show that the system has the potential to operate with a very low technician interaction under the zero-day attacks. We achieved 87:28% accuracy on the NSL-KDD's "KDDTest+" dataset and 76:61% accuracy on the challenging "KDDTest-21" with lower training time and lower needed computational resources.

cs.LG↗

arXiv2020

A Novel Dimension Reduction Scheme for Intrusion Detection Systems in IoT Environments

Internet of Things (IoT) brings new challenges to the security solutions of computer networks. So far, intrusion detection system (IDS) is one of the effective security tools, but the vast amount of data that is generated by heterogeneous protocols and "things" alongside the constrained resources of the hosts, make some of the present IDS schemes defeated. To grant IDSs the ability of working in the IoT environments, in this paper, we propose a new distributed dimension reduction scheme which addresses the limited resources challenge. A novel autoencoder (AE) designed, and it learns to generate a latent space. Then, the constrained hosts/probes use the generated weights to lower the dimension with a single operation. The compressed data is transferred to a central IDS server to verify the traffic type. This scheme aims to lower the needed bandwidth to transfer data by compressing it and also reduce the overhead of the compression task in the hosts. The proposed scheme is evaluated on three well-known network traffic datasets (UNSW-NB15, TON\_IoT20 and NSL-KDD), and the results show that we can have a 3-dimensional latent space (about 90\% compression) without any remarkable fall in IDS detection accuracy.

cs.CR↗

arXiv2018

A new optimization problem in FSO communication system

According to the physical phenomena of atmospheric channels and wave propagation, performance of wireless communication systems can be optimized by simply adjusting its parameters. This way is more economically favorable than consuming power or using processing techniques. In this paper for the first time an optimization problem is developed on the performance of free-space optical multi-input multi-output (FSO-MIMO) communication system. Also it is the first time that the optimization of FSO is developed under saturated atmospheric turbulences. In order to get closer to the actual results, the effect of pointing error is taken into considerations. Assuming MPSK, DPSK modulation schemes, new closed-form expressions are derived for Bit Error Rate (BER) of the proposed structure. Furthermore, an optimization is developed taking into account the beam width as the variable parameter, and BER as the objective function, there is no constraint in this system. The obtained results can be a useful outcome for FSO-MIMO system designers in order to limit effects of pointing error as well as atmospheric turbulences and thus achieves optimum performance.

eess.SP↗

arXiv2017

On the Construction of Polar Codes for Achieving the Capacity of Marginal Channels

Achieving security against adversaries with unlimited computational power is of great interest in a communication scenario. Since polar codes are capacity achieving codes with low encoding-decoding complexity and they can approach perfect secrecy rates for binary-input degraded wiretap channels in symmetric settings, they are investigated extensively in the literature recently. In this paper, a polar coding scheme to achieve secrecy capacity in non-symmetric binary input channels is proposed. The proposed scheme satisfies security and reliability conditions. The wiretap channel is assumed to be stochastically degraded with respect to the legitimate channel and message distribution is uniform. The information set is sent over channels that are good for Bob and bad for Eve. Random bits are sent over channels that are good for both Bob and Eve. A frozen vector is chosen randomly and is sent over channels bad for both. We prove that there exists a frozen vector for which the coding scheme satisfies reliability and security conditions and approaches the secrecy capacity. We further empirically show that in the proposed scheme for non-symmetric binary-input discrete memoryless channels, the equivocation rate achieves its upper bound in the whole capacity-equivocation region.

cs.IT↗

arXiv2017

Polar Coding for Achieving the Capacity of Marginal Channels in Nonbinary-Input Setting

Achieving information-theoretic security using explicit coding scheme in which unlimited computational power for eavesdropper is assumed, is one of the main topics is security consideration. It is shown that polar codes are capacity achieving codes and have a low complexity in encoding and decoding. It has been proven that polar codes reach to secrecy capacity in the binary-input wiretap channels in symmetric settings for which the wiretapper's channel is degraded with respect to the main channel. The first task of this paper is to propose a coding scheme to achieve secrecy capacity in asymmetric nonbinary-input channels while keeping reliability and security conditions satisfied. Our assumption is that the wiretap channel is stochastically degraded with respect to the main channel and message distribution is unspecified. The main idea is to send information set over good channels for Bob and bad channels for Eve and send random symbols for channels that are good for both. In this scheme the frozen vector is defined over all possible choices using polar codes ensemble concept. We proved that there exists a frozen vector for which the coding scheme satisfies reliability and security conditions. It is further shown that uniform distribution of the message is the necessary condition for achieving secrecy capacity.

cs.IT↗

arXiv2014

CB-REFIM: A Practical Coordinated Beamforming in Multicell Networks

Performance of multicell systems is inevitably limited by interference and available resources. Although intercell interference can be mitigated by Base Station (BS) Coordination, the demand on inter-BS information exchange and computational complexity grows rapidly with the number of cells, subcarriers, and users. On the other hand, some of the existing coordination beamforming methods need computation of pseudo-inverse or generalized eigenvector of a matrix, which are practically difficult to implement in a real system. To handle these issues, we propose a novel linear beamforming across a set of coordinated cells only with limiting backhaul signalling. Resource allocation (i.e. precoding and power control) is formulated as an optimization problem with objective function of signal-to-interference-plus-noise ratios (SINRs) in order to maximize the instantaneous weighted sum-rate subject to power constraints. Although the primal problem is nonconvex and difficult to be optimally solved, an iterative algorithm is presented based on the Karush-Kuhn-Tucker (KKT) condition. To have a practical solution with low computational complexity and signalling overhead, we present CB-REFIM (coordination beamforming-reference based interference management) and show the recently proposed REFIM algorithm can be interpreted as a special case of CB-REFIM. We evaluate CB-REFIM through extensive simulation and observe that the proposed strategies achieve close-to-optimal performance.

cs.IT↗

arXiv2012

Secure FSM- based arithmetic codes

Recently, arithmetic coding has attracted the attention of many scholars because of its high compression capability. Accordingly, in this paper a method which adds secrecy to this well-known source code is proposed. Finite state arithmetic code (FSAC) is used as source code to add security. Its finite state machine (FSM) characteristic is exploited to insert some random jumps during source coding process. In addition, a Huffman code is designed for each state to make decoding possible even in jumps. Being Prefix free, Huffman codes are useful in tracking correct states for an authorized user when s/he decodes with correct symmetric pseudo random key. The robustness of our proposed scheme is further reinforced by adding another extra uncertainty by swapping outputs of Huffman codes in each state. Several test images are used for inspecting the validity of the proposed Huffman Finite State Arithmetic Coding (HFSAC). The results of several experimental, key space analyses, statistical analysis, key sensitivity and plaintext sensitivity tests show that HFSAC with a little effect on compression efficiency for image cryptosystem provides an efficient and secure way for real-time image encryption and transmission.

cs.CR↗