Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Janne J. Lehtomaki"'
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 3170-3184 (2024)
Gathering useful and trustworthy wireless data using crowdsourcing to train/validate machine learning (ML) algorithms can be difficult due to two factors: 1) correctness and reliability of the gathered data from various independent wireless access po
Externí odkaz:
https://doaj.org/article/cb676827022f43f0a94bec48548e958d
Publikováno v:
IEEE Access, Vol 11, Pp 6305-6319 (2023)
Accurate threshold setting for energy detector is important for example in dynamic spectrum access. This requires accurate statistical distribution models of the observed energy. In this paper, we consider energy detection (ED) for $M$ -ary quadratur
Externí odkaz:
https://doaj.org/article/8270fad19eed41abbba6aae80ff4d86b
Publikováno v:
IEEE Access, Vol 10, Pp 60610-60621 (2022)
Deep learning based channel estimation techniques have recently found an overwhelming interest owing to data-driven learning-based adaptability compared to conventional estimation techniques which rely on model-based approach. This paper exploits the
Externí odkaz:
https://doaj.org/article/518d5d7f04af47e69a2cb11d50639bc9
Publikováno v:
IEEE Access, Vol 10, Pp 34945-34959 (2022)
Deep learning (DL) driven proactive resource allocation (RA) is a promising approach for the efficient management of network resources. However, DL models typically have a limitation that they do not capture the uncertainty due to the arrival of new
Externí odkaz:
https://doaj.org/article/3f23e01f8d3f4ac5a339e4073810ec0b
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 1, Pp 777-797 (2020)
Wireless traffic usage forecasting methods can help to facilitate proactive resource allocation solutions in cloud managed wireless networks. In this paper, we present temporal and spatial analysis of network traffic using real traffic data of an ent
Externí odkaz:
https://doaj.org/article/1c9f2d99dec945f18a2d2a534509c280
Autor:
Zaheer Khan, Janne J. Lehtomaki
Publikováno v:
IEEE Access, Vol 8, Pp 4383-4396 (2020)
A wide range of new ultra reliable low latency communication (URLLC) applications in next generation (NG) wireless systems demand real-time radio frequency (RF) data analytics of channel utilization (CU) that can help in making proactive resource all
Externí odkaz:
https://doaj.org/article/9c2547ef4d6149be9a52f77545b38407
Publikováno v:
IEEE Access, Vol 8, Pp 43301-43313 (2020)
Hardware accelerated modules that can continuously measure/analyze resource (frequency channels, power, etc.) utilization in real-time can help in achieving efficient network control, and configuration in cloud managed wireless networks. As utilizati
Externí odkaz:
https://doaj.org/article/530f86da270f4b4f858b6558b5254383
Publikováno v:
IEEE Access, Vol 8, Pp 173641-173653 (2020)
To facilitate efficient cloud managed resource allocation solutions, collection of key wireless metrics from multiple access points (APs) at different locations within a given area is required. In unlicensed shared spectrum bands collection of metric
Externí odkaz:
https://doaj.org/article/1f8e11732a5748158dc223a13fa6a5e7
Publikováno v:
IEEE Access, Vol 7, Pp 133725-133737 (2019)
We investigate the design of signal processing in wideband spectrum usage (SPU) measurements for efficient and smart dynamic spectrum access (DSA). In particular, we focus on spectrum usage detection (SPUD) in the experimental measurements. The detec
Externí odkaz:
https://doaj.org/article/404169f5d807463e8a73787a34b3ac70