Caching in Future Mobile Networks: Utilize Memory to Overcome Spectrum Shortage
Final Report Abstract
In future wireless networks, the higher data rate requirements by the users call for dense mobile infrastructure. In particular, more base stations are required to fulfill the demands of the users. This in turn put more constraints on the base stations to decide how to optimally assign available resources. Cloud and Fog Radio Access Networks (C-FRAN) are proposed as a new model to strengthen the limited computational complexity of the base stations. Since the central servers or clouds not only contain the data base of all the files, they also have more computational resources and can assist the base stations to fulfill the other desired tasks. Within this context, the project aimed at two important aspects, namely • how the necessary computation based on sensitive data can be distributed among those servers while ensuring privacy and • how to minimize the latency in providing the data from the clouds to the users. In particular, due to the broadcast nature of the wireless medium, the communication link between the base stations and the cloud, referred to as backhaul/fronthaul link, is limited by certain rate and latency constraints. The methods to investigate and diminish the issue of limited backhaul rate constraint in the project were two-fold. First, utilizing the leverage offered by caching, i.e., storing popular files (video e.g.) in mobile users’ local caches and/or edge nodes (e.g, base stations (BS) or relays) disseminated in the network coverage area: The local availability of requested user content in the caches, also referred to as cache hits, results in reduced backhaul traffic and low file delivery time. Second, the design of schemes to tradeoff between utilizing the backhaul/fronthaul links and the necessary distributed computation at the cloud servers. In the project, we have studied the fundamental information-theoretic limits in terms of lower and upper bounds on the delivery time. Cases in which simple zeroforcing (ZF) and more involved interference alignment (IA) schemes were needed were identified based on the bounds. Further, the designed schemes offered the opportunity to cast the research problem as optimization problems, which enabled uplink and downlink rate-efficient, straggler-robust and secure distributed computations.
Publications
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Delivery Time Minimization in Cache-Assisted Broadcast-Relay Wireless Networks with Imperfect CSI. 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 1-5. IEEE.
Kakar, Jaber; Chaaban, Anas; Sezgin, Aydin & Paulraj, Arogyaswami
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Delivery Time Minimization in Edge Caching: Synergistic Benefits of Subspace Alignment and Zero Forcing. 2018 IEEE International Conference on Communications (ICC), 1-6. IEEE.
Kakar, Jaber; Alameer, Alaa; Chaaban, Anas; Sezgin, Aydin & Paulraj, Arogyaswami
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Cache-Assisted Broadcast-Relay Wireless Networks: A Delivery-Time Cache-Memory Tradeoff. IEEE Access, 7(2019), 76833-76858.
Kakar, Jaber; Alameer, Ahmad Alaa; Chaaban, Anas; Sezgin, Aydin & Paulraj, Arogyaswami
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On the Capacity and Straggler-Robustness of Distributed Secure Matrix Multiplication. IEEE Access, 7(2019), 45783-45799.
Kakar, Jaber; Ebadifar, Seyedhamed & Sezgin, Aydin
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Uplink Cost Adjustable Schemes in Secure Distributed Matrix Multiplication. 2020 IEEE International Symposium on Information Theory (ISIT), 1124-1129. IEEE.
Kakar, Jaber; Khristoforov, Anton; Ebadifar, Seyedhamed & Sezgin, Aydin
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Codes Trading Upload for Download Cost in Secure Distributed Matrix Multiplication. IEEE Transactions on Communications, 69(8), 5409-5424.
Kakar, Jaber; Khristoforov, Anton; Ebadifar, Seyedhamed & Sezgin, Aydin
