20 research outputs found
Throughput Maximization in Cloud Radio Access Networks using Network Coding
This paper is interested in maximizing the total throughput of cloud radio
access networks (CRANs) in which multiple radio remote heads (RRHs) are
connected to a central computing unit known as the cloud. The transmit frame of
each RRH consists of multiple radio resources blocks (RRBs), and the cloud is
responsible for synchronizing these RRBS and scheduling them to users. Unlike
previous works that consider allocating each RRB to only a single user at each
time instance, this paper proposes to mix the flows of multiple users in each
RRB using instantly decodable network coding (IDNC). The proposed scheme is
thus designed to jointly schedule the users to different RRBs, choose the
encoded file sent in each of them, and the rate at which each of them is
transmitted. Hence, the paper maximizes the throughput which is defined as the
number of correctly received bits. To jointly fulfill this objective, we design
a graph in which each vertex represents a possible user-RRB association,
encoded file, and transmission rate. By appropriately choosing the weights of
vertices, the scheduling problem is shown to be equivalent to a maximum weight
clique problem over the newly introduced graph. Simulation results illustrate
the significant gains of the proposed scheme compared to classical coding and
uncoded solutions.Comment: 7 pages, 7 figure
Coalition Formation Game for Cooperative Content Delivery in Network Coding Assisted D2D Communications
Device-to-device (D2D) communications have shown a huge potential in cellular offloading and become a potential technology in 5G and beyond. In D2D networks, the requested contents by user devices (UDs) can be delivered via D2D links, thus offloading the content providers (CPs). In this work, we address the problem of minimizing the delay of delivering content in a decentralized and partially D2D connected network using network coding (NC) and cooperation among the UDs. The proposed optimization framework considers UDs’ acquired and missing contents, their limited coverage zones, NC, and content’s erasure probability. As such, the completion time for delivering all missing contents to all UDs is minimized. The problem is modeled as a coalition game with cooperative-players wherein the payoff function is derived so that increasing individual payoff results in the desired cooperative behavior. Given the intractability of the formulation, the coalition game is relaxed to a coalition formation game (CFG). A distributed coalition formation algorithm relying on merge-and-split rules is developed for solving the relaxed problem at each transmission. The effectiveness of the proposed solution is validated through computer simulation against existing schemes
Energy Efficient Communications in RIS-assisted UAV Networks Based on Genetic Algorithm
This paper proposes a solution for energy-efficient communication in
reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)
networks. The limited battery life of UAVs is a major concern for their
sustainable operation, and RIS has emerged as a promising solution to reducing
the energy consumption of communication systems. The paper formulates the
problem of maximizing the energy efficiency of the network as a mixed integer
non-linear program, in which UAV placement, UAV beamforming, On-Off strategy of
RIS elements, and phase shift of RIS elements are optimized. The proposed
solution utilizes the block coordinate descent approach and a combination of
continuous and binary genetic algorithms. Moreover, for optimizing the UAV
placement, Adam optimizer is used. The simulation results show that the
proposed solution outperforms the existing literature. Specifically, we
compared the proposed method with the successive convex approximation (SCA)
approach for optimizing the phase shift of RIS elements
Effectiveness of Reconfigurable Intelligent Surfaces to Enhance Connectivity in UAV Networks
Reconfigurable intelligent surfaces (RISs) are expected to make future 6G
networks more connected and resilient against node failures, due to their
ability to introduce controllable phase-shifts onto impinging electromagnetic
waves and impose link redundancy. Meanwhile, unmanned aerial vehicles (UAVs)
are prone to failure due to limited energy, random failures, or targeted
failures, which causes network disintegration that results in information
delivery loss. In this paper, we show that the integration between UAVs and
RISs for improving network connectivity is crucial. We utilize RISs to provide
path diversity and alternative connectivity options for information flow from
user equipments (UEs) to less critical UAVs by adding more links to the
network, thereby making the network more resilient and connected. To that end,
we first define the criticality of UAV nodes, which reflects the importance of
some nodes over other nodes. We then employ the algebraic connectivity metric,
which is adjusted by the reflected links of the RISs and their criticality
weights, to formulate the problem of maximizing the network connectivity. Such
problem is a computationally expensive combinatorial optimization. To tackle
this problem, we propose a relaxation method such that the discrete scheduling
constraint of the problem is relaxed and becomes continuous. Leveraging this,
we propose two efficient solutions, namely semi-definite programming (SDP)
optimization and perturbation heuristic, which both solve the problem in
polynomial time. For the perturbation heuristic, we derive the lower and upper
bounds of the algebraic connectivity obtained by adding new links to the
network. Finally, we corroborate the effectiveness of the proposed solutions
through extensive simulation experiments.Comment: 14 pages, 8 figures, journal paper. arXiv admin note: text overlap
with arXiv:2308.0467
Coalition Formation Game for Cooperative Content Delivery in Network Coding Assisted D2D Communications
Device-to-device (D2D) communications have shown a huge potential in cellular offloading and become a potential technology in 5G and beyond. In D2D networks, the requested contents by user devices (UDs) can be delivered via D2D links, thus offloading the content providers (CPs). In this work, we address the problem of minimizing the delay of delivering content in a decentralized and partially D2D connected network using network coding (NC) and cooperation among the UDs. The proposed optimization framework considers UDs’ acquired and missing contents, their limited coverage zones, NC, and content’s erasure probability. As such, the completion time for delivering all missing contents to all UDs is minimized. The problem is modeled as a coalition game with cooperative-players wherein the payoff function is derived so that increasing individual payoff results in the desired cooperative behavior. Given the intractability of the formulation, the coalition game is relaxed to a coalition formation game (CFG). A distributed coalition formation algorithm relying on merge-and-split rules is developed for solving the relaxed problem at each transmission. The effectiveness of the proposed solution is validated through computer simulation against existing schemes