With the development of artificial intelligence (AI) techniques, implementing AI-based techniques to improve wireless transceivers becomes an emerging research topic. Within this context, AI-based channel characterization and estimation become the focus since these methods have not been solved by traditional methods very well and have become the bottleneck of transceiver efficiency in large-scale orthogonal frequency division multiplexing (OFDM) systems. Specifically, by formulating channel estimation as a generative AI problem, generative AI methods such as diffusion models (DMs) can efficiently deal with rough initial estimations and have great potential to cooperate with traditional signal processing methods. This paper focuses on the transceiver design of OFDM systems based on DMs, provides an illustration of the potential of DMs in wireless transceivers, and points out the related research directions brought by DMs. We also provide a proof-of-concept case study of further adapting DMs for better wireless receiver performance.

Home » Technology » Applications and development 4 industries that will be transformed by machine learning in 2017 Feature 6 April 2017 Machine learning has become a huge trend in the technology industry in the last few years, as a more accessible side of artificial intelligence, with computers learning to complete tasks without being directly programmed to do so Nick Ismail In 2016 there were many machine learning pilots and trials in the industry, with acquisitions of machine learning start-ups by tech giants. Deep learning, a branch of machine learning that produces efficient algorithms to model high level data, is also becoming mainstream. Self-driving cars Perhaps the most popular application of machine learning in the consumer field of vision is in driverless cars technology. Many of these cars are currently in the testing phase, but the idea of self-driving cars on public roads is in its infancy. As self-driving cars take to the road, it will prove essential that they are able to respond to the situations around them in real time.

Centre for Connected and Autonomous Vehicles has announced that Businesses can apply for a share of up to £25 million to develop, demonstrate and trial technologies for connected and autonomous vehicles in real-world settings. The Centre for Connected and Autonomous Vehicles (CCAV) plans to invest up to £25 million in up to 4 pilot schemes for self-driving vehicles. Funding is for pilots of self-driving passenger vehicles which include at least a 6-month trial in a public or semi-controlled setting. Trials should have a clear commercial focus, with potential to become an enduring service, the centre has announced. CCAV was set up by the Department for Business, Energy and Industrial Strategy and the Department for Transport to help ensure the UK is a world leader in developing and testing connected and autonomous vehicles.

A new chair-based gymnastics exercise programme has significant benefits for people with dementia, says a report. More than 150 people have taken part in the Love to Move scheme run by the British Gymnastics Foundation (BGF). And research by Age UK found the scheme to have "demonstrable benefits in the physical, emotional and cognitive aspects of older people". The organisers now aim to train more people to deliver the programme and make it more widely available. "This age and dementia-friendly programme is astonishing people with its life-changing benefits," said BGF manager Patrick Bonner.

In 2016 there were many machine learning pilots and trials in the industry, with acquisitions of machine learning start-ups by tech giants. Deep learning, a branch of machine learning that produces efficient algorithms to model high level data, is also becoming mainstream. See also: Where does machine learning fit in the education sector? Perhaps the most popular application of machine learning in the consumer field of vision is in driverless cars technology. Many of these cars are currently in the testing phase, but the idea of self-driving cars on public roads is in its infancy.

In 2016 there were many machine learning pilots and trials in the industry, with acquisitions of machine learning start-ups by tech giants. Deep learning, a branch of machine learning that produces efficient algorithms to model high level data, is also becoming mainstream. See also: Where does machine learning fit in the education sector? Perhaps the most popular application of machine learning in the consumer field of vision is in driverless cars technology. Many of these cars are currently in the testing phase, but the idea of self-driving cars on public roads is in its infancy.

The first self-driving cars to be operated by ordinary British drivers will be left deliberately unmarked so that other drivers will not be tempted to "take them on", a senior car industry executive has revealed. One of the biggest fears of an ambitious project to lease the first autonomous vehicles to everyday motorists is that other road users might slam on their brakes or drive erratically in order to force the driverless cars into submission, he said. This is why the first 100 self-driving 4x4 vehicles to be leased to motorists as part of a pilot scheme on busy main roads into London will look no different than other Volvos of the same model, said Erik Coelingh, senior technical leader at Volvo Cars. The scheme will start in 2018. "From the outside you won't see that it's a self-driving car. From a purely scientific perspective it would be interesting to have some cars that are marked as self-driving cars and some that are not and see whether other road users react in a different way," Coelingh told the Observer.