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1. On the Multi-Activation Oriented Design of D2D-Aided Caching Networks

   Cai, Yang; Molisch, Andreas F. (January 2019, ... IEEE Global Communications Conference)

   Caching at the wireless edge has proven to be a promising approach for efficient video distribution, especially when aided by device-to-device communication. A widely explored scheme is to sub-divide a cell into clusters, and allow one pair of users within each cluster to communicate in each time slot. As more devices are raising frequent requests for popular videos, activating multiple links simultaneously can potentially improve the throughput. However, allowing multiple links at the same time requires to solve the problems of avoiding request clashes, i.e., multiple users requesting transmission from the same caching node, as well as interference management. To address these issues, this paper proposes new designs of both the caching policy and the transmission policy (i.e., link scheduling and power control). Furthermore, the duration of each time slot is optimized to improve the throughput. Finally, some numerical results demonstrate the performance gain of the proposed designs. 

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2. Simple Caching Schemes for Non-homogeneous MISO Cache-Aided Communication via Convexity

   https://doi.org/10.1109/ICASSP40776.2020.9053936  

   Bergel, Itsik; Mohajer, Soheil (May 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

   We present a novel scheme for cache-aided communication over multiple-input and single output (MISO) cellular networks. The presented scheme achieves the same number of degrees of freedom as known coded caching schemes, but, at much lower complexity. The scheme is derived for communication systems with heterogeneous rates and finite signal-to-noise ratio, in which links are modeled by wideband fading channels. The base station is serving multiple users simultaneously, by sending a combination of several packets, each intended for one user. The interference is either suppressed using the cache content or nulled by zero-forcing at the unintended users. We focus on efficient coding schemes, which allow for a maximum number of users to be served throughout the course of communication. An achievable rate region is characterized by determining the extreme rate vectors satisfying an efficient transmission. The analysis results in a simple scheduling scheme and in a closed-form performance analysis. 

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3. Unsupervised Detection via Artificial Dual-Path Transmission

   https://doi.org/10.1109/IEEECONF56349.2022.10051985  

   Hussain, Ahmed; Ibrahim, Mohamed Salah; Sidiropoulos, Nicholas D. (October 2022, 56th Asilomar Conference on Signals, Systems, and Computers)

   Channel estimation in rapidly time-varying or short and bursty communication scenarios is costly in terms of both pilot overhead and co-channel interference. In recent work, it was shown that multipath delay-diversity can be exploited to detect multiple co-channel user signals, provided that the relative multipath delays for the different users are distinct, and the two multipath ‘taps’ of each user have roughly commensurate power. These requirements may not hold naturally, however, especially for relatively narrowband or short-range transmissions with small delay spread. As an alternative, this paper advocates using dual antenna transmission in a manner that introduces artificial multipath and tight control of the power of the two channel taps, via baseband processing at the transmitter. The approach enjoys theoretical guarantees and affords simple decoding and accurate synchronization as a side bonus. Similar claims have been previously laid using packet repetition via a single transmit-antenna, but the dual-antenna artificial multipath scheme proposed herein doubles the transmission rate relative to packet repetition. Laboratory experiments using programmable radios are used to demonstrate successful operation of the proposed transmission scheme in practice. 

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4. Delay-aware Cellular Traffic Scheduling with Deep Reinforcement Learning

   https://doi.org/10.1109/GLOBECOM42002.2020.9322560  

   Zhang, Ticao; Shen, Shuyi; Mao, Shiwen; Chang, Gee-Kung (December 2020, GLOBECOM 2020 - 2020 IEEE Global Communications Conference)

   null (Ed.)

   Abstract: Radio access network (RAN) in 5G is expected to satisfy the stringent delay requirements of a variety of applications. The packet scheduler plays an important role by allocating spectrum resources to user equipments (UEs) at each transmit time interval (TTI). In this paper, we show that optimal scheduling is a challenging combinatorial optimization problem, which is hard to solve within the channel coherence time with conventional optimization methods. Rule-based scheduling methods, on the other hand, are hard to adapt to the time-varying wireless channel conditions and various data request patterns of UEs. Recently, integrating artificial intelligence (AI) into wireless networks has drawn great interest from both academia and industry. In this paper, we incorporate deep reinforcement learning (DRL) into the design of cellular packet scheduling. A delay-aware cell traffic scheduling algorithm is developed to map the observed system state to scheduling decision. Due to the huge state space, a recurrent neural network (RNN) is utilized to approximate the optimal action-policy function. Different from conventional rule-based scheduling methods, the proposed scheme can learn from the interactions with the environment and adaptively choosing the best scheduling decision at each TTI. Simulation results show that the DRL-based packet scheduling can achieve the lowest average delay compared with several conventional approaches. Meanwhile, the UEs' average queue lengths can also be significantly reduced. The developed method also exhibits great potential in real-time scheduling in delay-sensitive scenarios. 

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5. Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider’s Perspective

   https://doi.org/10.1109/WCNC45663.2020.9120507  

   Choi, Minseok; Molisch, Andreas F.; Han, Dong-Jun; Kim, Joongheon; Moon, Jaekyun (May 2020, 2020 IEEE Wireless Communications and Networking Conference (WCNC))

   In wireless caching networks, a user generally has a concrete purpose of consuming contents in a certain preferred category, and requests multiple contents in sequence. While most existing research on wireless caching and delivery has focused only on one-shot requests, the popularity distribution of contents requested consecutively is definitely different from the one-shot request and has been not considered. Also, especially from the perspective of the service provider, it is advantageous for users to consume as many contents as possible. Thus, this paper proposes two cache allocation policies for categorized contents and consecutive user demands, which maximize 1) the cache hit rate and 2) the number of consecutive content consumption, respectively. Numerical results show how categorized contents and consecutive content requests have impacts on the cache allocation. 

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