Proactive Jamming Toward Interference Alignment Networks: Beneficial and Adversarial Aspects

Abstract

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Secure Beamforming Design for Rate-Splitting Multiple Access in Multi-antenna Broadcast Channel with Confidential Messages

“…First proposed by Shannon [8] and later developed by Wyner [9], physical layer security has evolved from point-to-point systems [10,11] to multi-user systems [12], where interference is inevitable as the data streams intended to different users share the same time-frequency resource. Therefore, there are growing research interests in studying the effect of multi-user interference (MUI) on secure communications [13][14][15][16][17][18][19]. Contrary to the opinion of treating MUI as a performance bottleneck, MUI generates two contrasting effects on communication security: on the one hand, it impedes a certain legitimate user from decoding its desired data because of the aliasing of the useful signal and the interference; on the other hand, MUI adds to the difficulty for eavesdroppers to wiretap confidential data.…”

“…Consequently, properly managed MUI can be leveraged to enhance communication security. Based on this fact, many works [14][15][16][17][18][19] have been devoted to explore the benefits of MUI in intercepting undesired users as well as avoiding the performance loss of desired users in secure communications. Authors in [14] and [16] proposed interference alignment (IA) to eliminate the MUI to undesired legitimate users and disrupt eavesdroppers.…”

“…Based on this fact, many works [14][15][16][17][18][19] have been devoted to explore the benefits of MUI in intercepting undesired users as well as avoiding the performance loss of desired users in secure communications. Authors in [14] and [16] proposed interference alignment (IA) to eliminate the MUI to undesired legitimate users and disrupt eavesdroppers. Existing works mainly adopt the interference management approach where each user directly decodes the intended stream and treats the interference from the rest of legitimate users as noise.…”

Weighted Sum-Rate Maximization for Rate-Splitting Multiple Access Based Secure Communication

“…Considering this, many works have been devoted to explore how to benefit secure communications from MUI in intercepting undesired users and in the meantime avoid the performance loss of desired users. For instance, researchers in [5] and [6] proposed interference alignment (IA) to eliminate the interference to undesired legitimate users and meanwhile disrupt eavesdroppers by jointly designing beamforming matrices of transceivers.…”

Secure Transmission for Interference Networks: User Selection and Transceiver Design

“…In [24], two IA-based anti-eavesdropping schemes were proposed to guarantee the secure transmission via zero-forcing or AN, respectively, with or without the eavesdropping channel state information (CSI). In [25], beneficial jamming was leveraged via IA to protect the security of legitimate interference networks. However, the performance of IA is not optimal, due to the fact that interference alignment does not maximize the signal-to-interference-plusnoise ratio (SINR).…”