Results 51 to 60 of about 400 (179)
UAVs‐Assisted Low‐Bit Quantized CF‐mMIMO Systems With MmWave Communications Under MRC Detection
ABSTRACT The cell‐free massive multiple input multiple output (CF‐mMIMO) approach, due to its high coverage and the ability to attenuate the large‐scale fading impacts in wireless communications, has drawn a lot of attention. Additionally, because of their movement ability, low power, and low‐cost employed infrastructures, unmanned aerial vehicles ...
Sogol Moshirvaziri, Jamshid Abouei
wiley +1 more source
We introduce a fully distributed framework that leverages belief‐desire‐intention extended (BDIx) agents on user devices to perform dynamic clustering and access‐point selection in a cell‐free 6G network, using both classical and deep‐learning methods for deterministic, scalable AP grouping.
Iakovos Ioannou +5 more
wiley +1 more source
In emergency situations where ground base stations are disabled, UAVs, due to their low cost and high adaptability, restore communication coverage in remote areas. The main challenge is optimally determining the three‐dimensional positions of the UAVs to meet dynamic user demand and reduce interference.
Nooshin Boroumand Jazi +2 more
wiley +1 more source
Accurate Fault Location Using Deep Belief Network for Optical Fronthaul Networks in 5G and Beyond
In face of staggering traffic growth driven by fifth generation (5G) and beyond, optical fronthaul networks which host such connections require efficient and reliable operational environments. Fault location has become one of the primary factors for post-
Ao Yu +7 more
doaj +1 more source
Testbed Verification of New Fronthaul Technology for 5G Systems [PDF]
The fronthaul for 5th generation mobile systems (and beyond) has evolved with new splits for the radio access network functions defined, and the transport for these split interfaces having very different requirements. Testing of the transport for such split interfaces is reported, and it is shown that an Ethernet fronthaul transport network, which is ...
Nathan J. Gomes +10 more
openaire +1 more source
IoT‐5G and B5G/6G resource allocation and network slicing orchestration using learning algorithms
In this article, the challenges related to the evolution of 5G and B5G/6G networks are examined more closely. The authors then primarily focus on machine learning solutions for resource allocation in 5G and B5G/6G networks. The requirements for dynamic network slicing orchestration are also analysed.
Ado Adamou Abba Ari +5 more
wiley +1 more source
All-Optical Network Capacity for 5G Cellular Fronthaul
In this paper, we have investigated the use of fast wavelength switching optical transmitters and a wavelength selective space switching all-optical network for cellular fronthaul applications. System capacity is calculated by using hard-deadlines that arise from the radio requirements and the physical constraints of the optical network.
Philip Perry +5 more
openaire +2 more sources
Joint Weighted Dynamic Resources Optimisation in Green Open Radio Access Network
The paper presents an optimisation framework for the off‐grid green open radio access network architecture using renewable energy, aiming to optimise power and bandwidth allocation, ensure high data rates and improve service quality, considering factors like power consumption and maintenance cost. ABSTRACT The rapid growth of interconnected devices and
Raad S. Alhumaima +3 more
wiley +1 more source
5G Fronthaul–Latency and Jitter Studies of CPRI Over Ethernet [PDF]
Common Public Radio Interface (CPRI) is a successful industry cooperation defining the publicly available specification for the key internal interface of radio base stations between the radio equipment control (REC) and the radio equipment (RE) in the fronthaul of mobile networks.
Divya Chitimalla +4 more
openaire +6 more sources
The paper proposes a containerised edge computing model for power optimisation in 6G‐inspired massive Internet‐of‐Things applications. The problem is formulated as a central processing unit energy consumption cost function based on quasi‐finite system observations. Results show that the model performs better compared to a competitive baseline algorithm.
Babatunde S. Awoyemi +1 more
wiley +1 more source

