Signal transmission in optical networks suffers from physical layer impairments, which are diversified in nature and cumulative from end-to-end.
This paper explores the feasibility of leveraging deep reinforcement learning (DRL) to enable dynamic resource management in Wi-Fi networks implementing distributed multi-user MIMO (D-MIMO).
The decision processes surrounding outsourcing are complicated by the very nature of uncertainty involved in the outsourcing process and by poor vendor management.
In enterprise networks, network functions such as address translation, firewall and deep packet inspection are often implemented in middleboxes.
In this paper we have addressed some of the key design issues associated with providing multimedia service over wireless networks.
The classic optimal transportation problem consists in finding the most cost-effective way of moving masses from one set of locations to another, minimizing its transportation cost.
The classic optimal transportation problem consists in finding the most cost-effective way of moving masses from one set of locations to another, minimizing its transportation cost.
In order to cope with the rapidly increasing video traffic (both downloaded and streamed) resulting from Internet TV, a telecommunications company (telco) can deploy a network of caches, which sit
This paper studies the use of optimum combining to increase the capacity of narrowband in-building radio communication systems with multiple users.
This paper studies the use of optimum combining to increase the capacity of narrowband in-building radio communication systems with multiple users.
