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Shahid Mehraj Shah

Publications and source records attributed to Shahid Mehraj Shah.

8 recordsLinked to original sources
arXiv2023

Bayesian Game Formulation of Power Allocation in Multiple Access Wiretap Channel with Incomplete CSI

In this paper, we address the problem of distributed power allocation in a $K$ user fading multiple access wiretap channel, where global channel state information is limited, i.e., each user has knowledge of their own channel state with respect to Bob and Eve but only knows the distribution of other users' channel states. We model this problem as a Bayesian game, where each user is assumed to selfishly maximize his average \emph{secrecy capacity} with partial channel state information. In this work, we first prove that there is a unique Bayesian equilibrium in the proposed game. Additionally, the price of anarchy is calculated to measure the efficiency of the equilibrium solution. We also propose a fast convergent iterative algorithm for power allocation. Finally, the results are validated using simulation results.

cs.IT↗
arXiv2023

Achievable Sum-rate of variants of QAM over Gaussian Multiple Access Channel with and without security

The performance of next generation wireless systems (5G/6G and beyond) at the physical layer is primarily driven by the choice of digital modulation techniques that are bandwidth and power efficient, while maintaining high data rates. Achievable rates for Gaussian input and some finite constellations (BPSK/QPSK/QAM) are well studied in the literature. However, new variants of Quadrature Amplitude Modulation (QAM) such as Cross-QAM (XQAM), Star-QAM (S-QAM), Amplitude and phase shift keying (APSK), and Hexagonal Quadrature Amplitude Modulation (H-QAM) are not studied in the context of achievable rates for meeting the demand of high data rates. In this paper, we study achievable rate region for different variants of M-QAM like Cross-QAM, H-QAM, Star-QAM and APSK. We also compute mutual information corresponding to the sum rate of Gaussian Multiple Access Channel (G-MAC), for hybrid constellation scheme, e.g., user 1 transmits using Star-QAM and user 2 by H-QAM. From the results, it is observed that S-QAM gives the maximum sum-rate when users transmit same constellations. Also, it has been found that when hybrid constellation is used, the combination of Star-QAM \& H-QAM gives the maximum rate. In the next part of the paper, we consider a scenario wherein an adversary is also present at the receiver side and is trying to decode the information. We model this scenario as Gaussian Multiple Access Wiretap Channel (G-MAW-WT). We then compute the achievable secrecy sum rate of two user G-MAC-WT with discrete inputs from different variants of QAM (viz, X-QAM, H-QAM and S-QAM).It has been found that at higher values of SNR, S-QAM gives better values of SSR than the other variants. For hybrid inputs of QAM, at lower values of SNR, combination of APSK and S-QAM gives better results and at higher values of SNR, combination of HQAM and APSK gives greater value of SSR.

cs.IT↗
arXiv2023

Construction of non-CSS quantum codes using measurements on cluster states

The Measurement-based quantum computation provides an alternate model for quantum computation compared to the well-known gate-based model. It uses qubits prepared in a specific entangled state followed by single-qubit measurements. The stabilizers of cluster states are well defined because of their graph structure. We exploit this graph structure extensively to design non-CSS codes using measurement in a specific basis on the cluster state. % We aim to construct $[[n,1]]$ non-CSS code from a $(n+1)$ qubit cluster state. The procedure is general and can be used specifically as an encoding technique to design any non-CSS codes with one logical qubit. We show there exists a $(n+1)$ qubit cluster state which upon measurement gives the desired $[[n,1]]$ code.

quant-ph↗
arXiv2022

Unsupervised Ensemble Based Deep Learning Approach for Attack Detection in IoT Network

The Internet of Things (IoT) has altered living by controlling devices/things over the Internet. IoT has specified many smart solutions for daily problems, transforming cyber-physical systems (CPS) and other classical fields into smart regions. Most of the edge devices that make up the Internet of Things have very minimal processing power. To bring down the IoT network, attackers can utilise these devices to conduct a variety of network attacks. In addition, as more and more IoT devices are added, the potential for new and unknown threats grows exponentially. For this reason, an intelligent security framework for IoT networks must be developed that can identify such threats. In this paper, we have developed an unsupervised ensemble learning model that is able to detect new or unknown attacks in an IoT network from an unlabelled dataset. The system-generated labelled dataset is used to train a deep learning model to detect IoT network attacks. Additionally, the research presents a feature selection mechanism for identifying the most relevant aspects in the dataset for detecting attacks. The study shows that the suggested model is able to identify the unlabelled IoT network datasets and DBN (Deep Belief Network) outperform the other models with a detection accuracy of 97.5% and a false alarm rate of 2.3% when trained using labelled dataset supplied by the proposed approach.

cs.IT↗
arXiv2016

Achieving Shannon Capacity in a Wiretap Channel via Previous Messages

In this paper we consider a wiretap channel with a secret key buffer. We use the coding scheme of [1] to enhance the secrecy rate to the capacity of the main channel, while storing each securely transmitted message in the secret key buffer. We use the oldest secret bits from the buffer to be used as a secret key to transmit a message in a slot and then remove those bits. With this scheme we are able to prove stronger results than those in [1]. i.e., not only the message which is being transmitted currently, but all the messages transmitted in last $N_1$ slots are secure with respect to all the information that the eavesdropper possesses, where $N_1$ can be chosen arbitrarily large.

cs.IT↗
arXiv2016

Resource Allocation in a MAC with and without security via Game Theoretic Learning

In this paper a $K$-user fading multiple access channel with and without security constraints is studied. First we consider a F-MAC without the security constraints. Under the assumption of individual CSI of users, we propose the problem of power allocation as a stochastic game when the receiver sends an ACK or a NACK depending on whether it was able to decode the message or not. We have used Multiplicative weight no-regret algorithm to obtain a Coarse Correlated Equilibrium (CCE). Then we consider the case when the users can decode ACK/NACK of each other. In this scenario we provide an algorithm to maximize the weighted sum-utility of all the users and obtain a Pareto optimal point. PP is socially optimal but may be unfair to individual users. Next we consider the case where the users can cooperate with each other so as to disagree with the policy which will be unfair to individual user. We then obtain a Nash bargaining solution, which in addition to being Pareto optimal, is also fair to each user. Next we study a $K$-user fading multiple access wiretap Channel with CSI of Eve available to the users. We use the previous algorithms to obtain a CCE, PP and a NBS. Next we consider the case where each user does not know the CSI of Eve but only its distribution. In that case we use secrecy outage as the criterion for the receiver to send an ACK or a NACK. Here also we use the previous algorithms to obtain a CCE, PP or a NBS. Finally we show that our algorithms can be extended to the case where a user can transmit at different rates. At the end we provide a few examples to compute different solutions and compare them under different CSI scenarios.

cs.IT↗