Enhancing Physical Layer Security in AF Relay Assisted Multi-Carrier Wireless Transmission

In this paper, we study the physical layer security (PLS) problem in the dual hop orthogonal frequency division multiplexing (OFDM) based wireless communication system. First, we consider a single user single relay system and study a joint power optimization problem at the source and relay subject to individual power constraint at the two nodes. The aim is to maximize the end to end secrecy rate with optimal power allocation over different sub-carriers. Later, we consider a more general multi-user multi-relay scenario. Under high SNR approximation for end to end secrecy rate, an optimization problem is formulated to jointly optimize power allocation at the BS, the relay selection, sub-carrier assignment to users and the power loading at each of the relaying node. The target is to maximize the overall security of the system subject to independent power budget limits at each transmitting node and the OFDMA based exclusive sub-carrier allocation constraints. A joint optimization solution is obtained through duality theory. Dual decomposition allows to exploit convex optimization techniques to find the power loading at the source and relay nodes. Further, an optimization for power loading at relaying nodes along with relay selection and sub carrier assignment for the fixed power allocation at the BS is also studied. Lastly, a sub-optimal scheme that explores joint power allocation at all transmitting nodes for the fixed subcarrier allocation and relay assignment is investigated. Finally, simulation results are presented to validate the performance of the proposed schemes.Comment: 10 pages, 7 figures, accepted in Transactions on Emerging Telecommunications Technologies (ETT), formerly known as European Transactions on Telecommunications (ETT

A Learning Based Framework for Enhancing Physical Layer Security in Cooperative D2D Network

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device (D2D) communication with spectrum reuse offers a potential solution to spectrum scarcity. On the other hand, non-orthogonal multiple access (NOMA) as a multiple-access approach has emerged as a key technology to re-use a spectrum among multiple users. A cellular users (CUs) can share their spectrum with D2D users (DUs) and in response, the D2D network can help relay the CU signal to achieve better secrecy from an eavesdropper. Power optimization is known to be a promising technique to enhance system performance in challenging communication environments. This work aimed to enhance the secrecy rate of the CUs where the D2D transmitter (DT) helps in relaying the CU’s message under the amplify and forward (AF) protocol. A power optimization problem is considered under the quality of service constraints in terms of minimum rate requirements at the receivers and maximum power budgets at the transmitters. The problem is a non-convex complex optimization. A deep learning-based solution is proposed and promising results are obtained in terms of the secrecy rate of CU and the rate of D2D users

A Learning Based Framework for Enhancing Physical Layer Security in Cooperative D2D Network

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device (D2D) communication with spectrum reuse offers a potential solution to spectrum scarcity. On the other hand, non-orthogonal multiple access (NOMA) as a multiple-access approach has emerged as a key technology to re-use a spectrum among multiple users. A cellular users (CUs) can share their spectrum with D2D users (DUs) and in response, the D2D network can help relay the CU signal to achieve better secrecy from an eavesdropper. Power optimization is known to be a promising technique to enhance system performance in challenging communication environments. This work aimed to enhance the secrecy rate of the CUs where the D2D transmitter (DT) helps in relaying the CU’s message under the amplify and forward (AF) protocol. A power optimization problem is considered under the quality of service constraints in terms of minimum rate requirements at the receivers and maximum power budgets at the transmitters. The problem is a non-convex complex optimization. A deep learning-based solution is proposed and promising results are obtained in terms of the secrecy rate of CU and the rate of D2D users

An efficient security method based on exploiting channel state information (CSI)

A channel amplitude quantization method that can effectively quantize the channel response using just one single threshold value is proposed in order to extract a random manipulating sequence with good secrecy properties. Specifically, a Time Division Duplex (TDD) wireless system is considered over independent identical distributed (i.i.d.) Rayleigh fast fading channel, where potential passive eavesdroppers (Eves) can only estimate their own channel and have no knowledge about CSI between legitimate communication parties. The transmitter (Alice) is only aware of the CSI of the legitimate user (Bob). Particularly, the proposed security technique takes the bits of the transmitted data packets and manipulate them with a logical vector that characterizes the channel randomness based on the estimated CSI gain. The process of manipulation is implemented on a bit level basis using an XOR operation exactly before modulation process. The same XOR operation is implemented after demodulation process on the detected bits to extract the concealed bits. The obtained simulation results show that the employment of such mechanism can ensure data confidentiality. Furthermore, the simulation results are extended to include the effect of the selected quantization threshold on the BER performance of Eve as well as the amount of information leakage to its side. It is shown that security gap region between Bob and Eve is made very large over all expected Signal to Noise ratio (SNR) values despite the small degradation in the bit error rate (BER) performance of Bob because of the expected channel estimation errors due to noise