Joint Beamforming and Power Control for D2D-Assisted Integrated Sensing and Communication Networks

Integrated sensing and communication (ISAC) is an emerging technology in next-generation communication networks. However, the communication performance of the ISAC system may be severely affected by interference from the radar system if the sensing task has demanding performance requirements. In this paper, we exploit device-to-device communication (D2D) to improve system communication capacity. The ISAC system in a single cell D2D assisted-network is investigated, where the base station (BS) performs target sensing and communication with multiple celluar user equipments (CUEs) as well as D2D user equipments (DUEs) simultaneously communicating with other DUEs by multiplexing the same frequency resource. To achieve the optimal communication performance in the D2D-assisted ISAC system, a joint beamforming and power control problem is formulated with the goal to maximize the sum rate of the system while guaranteeing the performance requirements of radar sensing. Due to the non-convexity of the problem, we propose the algorithm to transform the origin problem into a relaxation form and obtain the solution. We also proposed the zero-forcing (ZF) beamforming scheme to acquire the solution that can eliminate the interference of the BS on DUEs. Extensive numerical simulations demonstrated that with the assistance of the D2D communications, our proposed algorithm significantly outperforms the baseline schemes in the system sum rate.

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?

How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,000 submitting authors and 9,000 submitted papers, we survey the authors on three questions: (i) their predicted probability of acceptance for each of their papers, (ii) their perceived ranking of their own papers based on scientific contribution, and (iii) the change in their perception about their own papers after seeing the reviews. The salient results are: (1) Authors have roughly a three-fold overestimate of the acceptance probability of their papers: The median prediction is 70% for an approximately 25% acceptance rate. (2) Female authors exhibit a marginally higher (statistically significant) miscalibration than male authors; predictions of authors invited to serve as meta-reviewers or reviewers are similarly calibrated, but better than authors who were not invited to review. (3) Authors' relative ranking of scientific contribution of two submissions they made generally agree (93%) with their predicted acceptance probabilities, but there is a notable 7% responses where authors think their better paper will face a worse outcome. (4) The author-provided rankings disagreed with the peer-review decisions about a third of the time; when co-authors ranked their jointly authored papers, co-authors disagreed at a similar rate -- about a third of the time. (5) At least 30% of respondents of both accepted and rejected papers said that their perception of their own paper improved after the review process. The stakeholders in peer review should take these findings into account in setting their expectations from peer review.