In many communication networks, secrecy constraints usually incur an extra limit in capacity (or generalized degrees-of-freedom, GDoF), in the sense that a penalty in capacity (or GDoF) is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand the limits of secrecy constraints in communication networks. In this work, we focus on how to break the limits of secrecy constraints in communication networks, i.e., how to remove the penalty in GDoF due to the secrecy constraints. We begin with three basic settings: a two-user symmetric Gaussian interference channel with confidential messages, a symmetric Gaussian wiretap channel with a helper, and a two-user symmetric Gaussian multiple access wiretap channel. Interestingly, in this work we show that adding common randomness at the transmitters can totally remove the penalty in sum GDoF or GDoF region of the three settings considered here. The results reveal that adding common randomness at the transmitters is a powerful way to break the limits of secrecy constraints in communication networks. Common randomness can be generated offline. The role of the common randomness is to jam the information signal at the eavesdroppers, without causing too much interference at the legitimate receivers. To accomplish this role, a new method of Markov chain-based interference neutralization is proposed in the achievability schemes utilizing common randomness. From the practical point of view, we hope to use less common randomness to break the limits of secrecy constraints. With this motivation, for most of the cases we characterize the minimal GDoF of common randomness to break the limits of secrecy constraints, based on our derived converses.
In many communication networks, secrecy constraints usually incur an extra limit in capacity (or generalized degrees-of-freedom, GDoF), in the sense that a penalty in capacity (or GDoF) is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand the limits of secrecy constraints in communication networks. In this work, we focus on how to break the limits of secrecy constraints in communication networks, i.e., how to remove the penalty in GDoF due to the secrecy constraints. We begin with three basic settings: a two-user symmetric Gaussian interference channel with confidential messages, a symmetric Gaussian wiretap channel with a helper, and a two-user symmetric Gaussian multiple access wiretap channel. Interestingly, in this work we show that adding common randomness at the transmitters can totally remove the penalty in sum GDoF or GDoF region of the three settings considered here. The results reveal that adding common randomness at the transmitters is a powerful way to break the limits of secrecy constraints in communication networks. Common randomness can be generated offline. The role of the common randomness is to jam the information signal at the eavesdroppers, without causing too much interference at the legitimate receivers. To accomplish this role, a new method of Markov chain-based interference neutralization is proposed in the achievability schemes utilizing common randomness. From the practical point of view, we hope to use less common randomness to break the limits of secrecy constraints. With this motivation, for most of the cases we characterize the minimal GDoF of common randomness to break the limits of secrecy constraints, based on our derived converses.
In communication networks secrecy constraints usually incur an extra limit in capacity or generalized degrees-of-freedom (GDoF), in the sense that a penalty in capacity or GDoF is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand the limits of secrecy constraints in communication networks. In this work, we focus on how to remove the secrecy constraints in communication networks, i.e., how to remove the GDoF penalty due to secrecy constraints. We begin with three basic settings: a two-user symmetric Gaussian interference channel with confidential messages, a symmetric Gaussian wiretap channel with a helper, and a two-user symmetric Gaussian multiple access wiretap channel. Interestingly, in this work we show that adding common randomness at the transmitters can totally remove the penalty in GDoF or GDoF region of the three settings considered here. The results reveal that adding common randomness at the transmitters is a powerful way to remove the secrecy constraints in communication networks in terms of GDoF performance. Common randomness can be generated offline. The role of the common randomness is to jam the information signal at the eavesdroppers, without causing too much interference at the legitimate receivers. To accomplish this role, a new method of Markov chain-based interference neutralization is proposed in the achievability schemes utilizing common randomness. From the practical point of view, we hope to use less common randomness to remove secrecy constraints in terms of GDoF performance. With this motivation, for most of the cases we characterize the minimal GDoF of common randomness to remove secrecy constraints, based on our derived converses and achievability.
In communication networks secrecy constraints usually incur an extra limit in capacity or generalized degrees-of-freedom (GDoF), in the sense that a penalty in capacity or GDoF is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand the limits of secrecy constraints in communication networks. In this work, we focus on how to remove the secrecy penalty in communication networks, i.e., how to remove the GDoF penalty due to secrecy constraints. We begin with three basic settings: a two-user symmetric Gaussian interference channel with confidential messages, a symmetric Gaussian wiretap channel with a helper, and a two-user symmetric Gaussian multiple access wiretap channel. Interestingly, in this work we show that adding common randomness at the transmitters can totally remove the penalty in GDoF or GDoF region of the three settings considered here. The results reveal that adding common randomness at the transmitters is a powerful way to remove the secrecy penalty in communication networks in terms of GDoF performance. Common randomness can be generated offline before the real-time message communication. The role of the common randomness is to jam the information signal at the eavesdroppers, without causing too much interference at the legitimate receivers. To accomplish this role, a new method of Markov chain-based interference neutralization is proposed in the achievability schemes utilizing common randomness. From the practical point of view, we need to minimize the amount of common randomness used for removing the secrecy penalty in terms of GDoF performance. With this motivation, for most of the cases we characterize the minimal GDoF of common randomness to remove secrecy penalty, based on our derived converses and achievability.
In this work we consider common randomness-aided secure communications, where a limited common randomness is available at the transmitters. Specifically, we focus on a two-user interference channel with secrecy constraints and a wiretap channel with a helper, in the presence of a limited common randomness shared between the transmitters. For both settings, we characterize the optimal secure sum degrees-of-freedom (DoF) or secure DoF as a function of the DoF of common randomness. The results reveal that the secure sum DoF or secure DoF increases as the DoF of common randomness increases, bridging the gap between the extreme DoF point without common randomness and the other extreme DoF point with unlimited common randomness. The proposed scheme is a two-layer coding scheme, in which two sub-schemes are designed in two layers respectively, i.e., at two different power levels, utilizing common randomness in the first layer only. The role of common randomness is to jam partial information signal at the eavesdroppers, without causing interference at the legitimate receivers. To prove the optimality of the proposed scheme, a new converse is also derived in this work.
In many communication channels, secrecy constraints usually incur a penalty in capacity, as well as generalized degrees-of-freedom (GDoF). In this work we show an interesting observation that, adding a helper can totally remove the penalty in sum GDoF, for a two-user symmetric Gaussian interference channel. For the interference channel where each transmitter sends a message to an intended receiver without secrecy constraints, the sum GDoF is a well-known "W" curve, characterized by Etkin-Tse-Wang in 2008. If the secrecy constraints are imposed on this interference channel, where the message of each transmitter must be secure from the unintended receiver (eavesdropper), then a GDoF penalty is incurred and the secure sum GDoF is reduced to a modified "W" curve, derived by Chen recently. In this work we show that, by adding a helper into this interference channel with secrecy constraints, the secure sum GDoF turns out to be a "W" curve, which is the same as the sum GDoF of the setting without secrecy constraints. The proposed scheme is based on the cooperative jamming and a careful signal design such that the jamming signal of the helper is aligned at a specific direction and power level with the information signals of the transmitters, which allows to totally remove the penalty in GDoF due to the secrecy constraints. Furthermore, the estimation approaches of noise removal and signal separation due to the rational independence are used in the secure rate analysis.
In many communication channels, secrecy constraintsusuallyincur a penalty in capacity, as well as generalized degrees-of-freedom (GDoF). In this paper, we show an interesting observation that adding a helper cantotallyremove the penalty in sum GDoF for a two-user symmetric Gaussian interference channel. For the interference channel where each transmitter sends a message to an intended receiver without secrecy constraints, the sum GDoF is a well-known “W” curve, characterized by Etkin–Tse–Wang in 2008. If the secrecy constraints are imposed on this interference channel, where the message of each transmitter must be secure from the unintended receiver (eavesdropper), then a GDoF penalty is incurred and the secure sum GDoF is reduced to a modified “W” curve, derived by Chen recently. In this paper, we show that, by adding a helper into this interference channel with secrecy constraints, thesecuresum GDoF turns out to be a “W” curve, which is the same as the sum GDoF of the setting without secrecy constraints. The proposed scheme is based on the cooperative jamming and a careful signal design such that the jamming signal of the helper is aligned at a specific direction and power level with the information signals of the transmitters, which allows us to totally remove the penalty in GDoF due to the secrecy constraints. Furthermore, the estimation approaches of noise removal and signal separation due to the rational independence are used in the secure rate analysis.
Secure GDoF of K -User Gaussian Interference Channels: When Secrecy Incurs No Penalty