More Like this

1. Multi-user Beam Alignment in Presence of Multi-path

   https://doi.org/10.1109/CISS53076.2022.9751191  

   Torkzaban, Nariman; Khojastepour, Mohammad A.; Baras, John S. (March 2022, Proceedings of the IEEE CISS 2022: Conference on Information Sciences and Systems)

   To overcome the high pathloss and the intense shadowing in millimeterwave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with high beamforming gains. The mm Wave channel consists of a few spatial clusters each associated with an angle of departure (AoD). The narrow beams must be aligned with the channel AoDs to increase the beamforming gain. This is achieved through a procedure called beam alignment (BA). Most of the BA schemes in the literature consider channels with a single dominant path while in practice the channel has a few resolvable paths with different AoDs, hence, such BA schemes may not work correctly in the presence of multi-path or at the least do not exploit such multi path to achieve diversity or increase robustness. In this paper, we propose an efficient BA schemes in presence of multi-path. The proposed BA scheme transmits probing packets using a set of scanning beams and receives the feedback for all the scanning beams at the end of probing phase from each user. We formulate the BA scheme as minimizing the expected value of the average transmission beamwidth under different policies. The policy is defined as a function from the set of received feedback to the set of transmission beams (TB). In order to maximize the number of possible feedback sequences, we prove that the set of scanning beams (SB) has an special form, namely, Tulip Design. Consequently, we rewrite the minimization problem with a set of linear constraints and reduced number of variables which is solved by using an efficient greedy algorithm. 

   more » « less
2. Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents

   https://doi.org/10.18653/v1/D19-1210  

   Hessel, Jack; Lee, Lillian; Mimno, David (November 2019, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP))

   null (Ed.)

   Images and text co-occur constantly on the web, but explicit links between images and sentences (or other intra-document textual units) are often not present. We present algorithms that discover image-sentence relationships without relying on explicit multimodal annotation in training. We experiment on seven datasets of varying difficulty, ranging from documents consisting of groups of images captioned post hoc by crowdworkers to naturally-occurring user-generated multimodal documents. We find that a structured training objective based on identifying whether collections of images and sentences co-occur in documents can suffice to predict links between specific sentences and specific images within the same document at test time. 

   more » « less
3. Age of Information Optimization in Multi-Channel Based Multi-Hop Wireless Networks

   https://doi.org/10.1109/TMC.2022.3181038  

   Lou, Jiadong; Yuan, Xu; Sigdel, Purushottam; Qin, Xiaoqi; Kompella, Sastry; Tzeng, Nian-Feng (April 2022, IEEE Transactions on Mobile Computing)

   The proliferation of IoT devices, with various capabilities in sensing, monitoring, and controlling, has prompted diverse emerging applications, highly relying on effective delivery of sensitive information gathered at edge devices to remote controllers for timely responses. To effectively deliver such information/status updates, this paper undertakes a holistic study of AoI in multi-hop networks by considering the relevant and realistic factors, aiming for optimizing information freshness by rapidly shipping sensitive updates captured at a source to its destination. In particular, we consider the multi-channel with OFDM (orthogonal frequency-division multiplexing) spectrum access in multi-hop networks and develop a rigorous mathematical model to optimize AoI at destination nodes. Real-world factors, including orthogonal channel access, wireless interference, and queuing model, are taken into account for the very first time to explore their impacts on the AoI. To this end, we propose two effective algorithms where the first one approximates the optimal solution as closely as we desire while the second one has polynomial time complexity, with a guaranteed performance gap to the optimal solution. The developed model and algorithms enable in-depth studies on AoI optimization problems in OFDM-based multi-hop wireless networks. Numerical results demonstrate that our solutions enjoy better AoI performance and that AoI is affected markedly by those realistic factors taken into our consideration. 

   more » « less
4. Social Learning in Multi Agent Multi Armed Bandits

   https://doi.org/10.1145/3393691.3394217  

   Sankararaman, Abishek; Ganesh, Ayalvadi; Shakkottai, Sanjay (December 2019, Proceedings of the ACM on Measurement and Analysis of Computing Systems)
5. Optimization of SINR and Illumination Uniformity in Multi-LED Multi-Datastream VLC Networks

   https://doi.org/10.1109/TCCN.2020.2972310  

   Ibne Mushfique, Sifat; Alsharoa, Ahmad; Yuksel, Murat (September 2020, IEEE Transactions on Cognitive Communications and Networking)

   null (Ed.)