The security issue on the physical layer is of significant challenge yet of paramount importance for 5G communications. In some previous works, transmit power allocation has already been studied for orthogonal frequency division multiplexing (OFDM) secure communication with Gaussian channel inputs for both a single user and multiple users. Faced with peak transmission power constraints, we adopt discrete channel inputs (e.g., equiprobable Quadrature Phase Shift Keying (QPSK) with symmetry) in a practical communication system, instead of Gaussian channel inputs. Finite-alphabet inputs impose a more significant challenge as compared with conventional Gaussian random inputs for the multiuser wiretap OFDM systems. This paper considers the joint resource allocation in frequency-domain artificial noise (AN) assisted multiuser wiretap OFDM channels with discrete channel inputs. This security problem is formulated as nonconvex sum secrecy rate optimization by jointly optimizing the subcarrier allocation, information-bearing power, and AN-bearing power. To this end, with a suboptimal subcarrier allocation scheme, we propose an efficient iterative algorithm to allocate the power between the information and the AN via the Lagrange duality method. Finally, we carry out some numerical simulations to demonstrate the performance of the proposed algorithm.
The security issue on the physical layer is of significant challenge yet of paramount importance for 5G communications. In some previous works, transmit power allocation has already been studied for orthogonal frequency division multiplexing (OFDM) secure communication with Gaussian channel inputs for both a single user and multiple users. Faced with peak transmission power constraints, we adopt discrete channel inputs (e.g., equiprobable Quadrature Phase Shift Keying (QPSK) with symmetry) in a practical communication system, instead of Gaussian channel inputs. Finite-alphabet inputs impose a more significant challenge as compared with conventional Gaussian random inputs for the multiuser wiretap OFDM systems. This paper considers the joint resource allocation in frequency-domain artificial noise (AN) assisted multiuser wiretap OFDM channels with discrete channel inputs. This security problem is formulated as nonconvex sum secrecy rate optimization by jointly optimizing the subcarrier allocation, information-bearing power, and AN-bearing power. To this end, with a suboptimal subcarrier allocation scheme, we propose an efficient iterative algorithm to allocate the power between the information and the AN via the Lagrange duality method. Finally, we carry out some numerical simulations to demonstrate the performance of the proposed algorithm.
The security issue on the physical layer is of significant challenge yet paramount importance for 5G communications. In some previous works, transmit power allocation has already been studied for orthogonal frequency division multiplexing (OFDM) secure communication with Gaussian channel inputs for both a single user and multiple users. Facing with peak transmission power constraints, we adopt discrete channel inputs (e.g., QPSK) in practical communication system, instead of Gaussian channel inputs. Discrete channel inputs impose a more significant challenge as compared with conventional Gaussian channel inputs for the multiuser wiretap OFDM system. This paper considers the joint resource allocation for time-domain artificial noise (AN) aided multiuser wiretap orthogonal frequency-division multiplexing (OFDM) channels with discrete channel inputs, providing secure 5G communications. This security problem is formulated as nonconvex sum secrecy rate optimization by jointly optimizing the subcarrier allocation, information-bearing power and AN-bearing power. To this end, with suboptimal subcarrier allocation scheme, we develop an efficient iterative algorithm to allocate the power between the signal and the AN via the Lagrange duality method. Finally, we carry out some numerical simulation to demonstrate the performance of the proposed algorithms.
PHY-layer security is one of promising techniques for enhanced security and privacy protection in 5G communications. In this paper, the joint resource allocation and artificial noise (AN) design problem of multiuser wiretap orthogonal frequency-division multiplexing (OFDM) systems is investigated to improve the system secrecy rate and power efficiency, which can help to provide waveform design references for secure 5G communications. In such a multiuser wiretap OFDM system, one legitimate transmitter (Alice), multiple legitimate receivers (Bobs), and one eavesdropper (Eve) are simultaneously considered. The time-domain artificial noise is firstly involved to guarantee the target secrecy rates of multiple Bobs. Then a sum secrecy rate maximization problem with nonconvex integer nonlinear programming is formulated to jointly optimize the power, subcarrier allocation and AN design. To solve this tough problem with low computational complexity, a heuristical sub-optimal subcarrier allocation method is proposed, followed by the Lagrange dual method based joint power allocation and AN design scheme. Moreover, considering that sum secrecy rate maximization may result in unfairness for Bobs with bad channel gains, the transmit power minimization problem that ensures a target secrecy rate for each individual Bob is further addressed. An iterative algorithm is proposed to solve this power minimization problem by updating the subcarrier, power allocation and AN design alternatively. Numerical results demonstrate the effectiveness of the proposed algorithms.
Optimal power allocation for orthogonal frequency division multiplexing (OFDM) wiretap channels with Gaussian channel inputs has already been studied in some previous works from an information theoretical viewpoint. However, these results are not sufficient for practical system designs. One reason is that discrete channel inputs, such as quadrature amplitude modulation (QAM) signals, instead of Gaussian channel inputs, are deployed in current practical wireless systems to maintain moderate peak transmission power and receiver complexity. In this paper, we investigate the power allocation and artificial noise design for OFDM wiretap channels with discrete channel inputs. We first prove that the secrecy rate function for discrete channel inputs is nonconcave with respect to the transmission power. To resolve the corresponding nonconvex secrecy rate maximization problem, we develop a low-complexity power allocation algorithm, which yields a duality gap diminishing in the order of O(1/√N), where N is the number of subcarriers of OFDM. We then show that independent frequency-domain artificial noise cannot improve the secrecy rate of single-antenna wiretap channels. Towards this end, we propose a novel time-domain artificial noise design which exploits temporal degrees of freedom provided by the cyclic prefix of OFDM systems to jam the eavesdropper and boost the secrecy rate even with a single antenna at the transmitter. Numerical results are provided to illustrate the performance of the proposed design schemes.
In this paper, the resource allocation for multiuser wiretap Orthogonal Frequency-Division Multiplexing(OFDM) systems is investigated to improve the system power efficiency. In such a multiuser wiretap OFDM system, one legitimate transmitter (Alice), multiple legitimate receivers (Bobs), and one eavesdropper (Eve) are simultaneously considered. The time-domain artificial noise (AN) is firstly involved to guarantee the target secrecy rates of multiple Bobs. Different from the traditional sum secrecy rate maximization problem which may result in the unfair transition for Bobs with bad channel gains and more transmit power consumptions, a non-convex transmit power minimization problem is formulated to jointly optimize the power, subcarrier allocation and AN design, in which a target secrecy rate for each individual Bob is ensured. An iterative algorithm is further proposed to solve this power minimization problem by updating the subcarrier, power allocation and AN design alternatively. Numerical simulation results demonstrate the effectiveness of the proposal, including the improvements of system power efficiency and the fairness of multiple Bobs.
This paper considers an OFDM wiretap channel with a legitimate transmitter (Alice), multiple legitimate receivers (Bobs), and an eavesdropper (Eve). Alice simultaneously transmits confidential message to each individual Bob. The timedomain Artificial noise (AN) is firstly employed to the wiretap OFDM channel with multiple Bobs. Under the proposed AN approach, a nonconvex sum secrecy rate maximization problem is formulated to jointly optimize subcarrier allocation, power allocation and AN design. To solve this tough problem, the optimal subcarrier allocation is found at first, and then a low-complexity Lagrange dual method is developed to jointly optimize power allocation and AN design. Finally, numerical results demonstrate the effectiveness of the proposed algorithms, including power allocation gain, AN gain and multiuser gain.
In this paper, we study simultaneous wireless information and power transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA) systems with the coexistence of information receivers (IRs) and energy receivers (ERs). The IRs are served with best-effort secrecy data and the ERs harvest energy with minimum required harvested power. To enhance the physical layer security for IRs and yet satisfy energy harvesting requirements for ERs, we propose a new frequency-domain artificial noise (AN) aided transmission strategy. With the new strategy, we study the optimal resource allocation for the weighted sum secrecy rate maximization for IRs by power and subcarrier allocation at the transmitter. The studied problem is shown to be a mixed integer programming problem and thus nonconvex, while we propose an efficient algorithm for solving it based on the Lagrange duality method. To further reduce the computational complexity, we also propose a suboptimal algorithm of lower complexity. The simulation results illustrate the effectiveness of proposed algorithms as compared against other heuristic schemes.