Zobrazeno 71 - 80
of 2 109
pro vyhledávání: '"Larsson, Erik"'
This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL). The synchronous design relies on strict synchronization among users
Externí odkaz:
http://arxiv.org/abs/2112.11723
In a distributed multi-antenna system, multiple geographically separated transmit nodes communicate simultaneously to a receive node. Synchronization of these nodes is essential to achieve a good performance at the receiver. RadioWeaves is a new para
Externí odkaz:
http://arxiv.org/abs/2112.00592
This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or appro
Externí odkaz:
http://arxiv.org/abs/2111.15568
Publikováno v:
IEEE Transactions on Communications, Vol. 69, No. 11, pp. 7520 - 7530, November 2021
Future wireless networks need to support massive machine type communication (mMTC) where a massive number of devices accesses the network and massive MIMO is a promising enabling technology. Massive access schemes have been studied for co-located mas
Externí odkaz:
http://arxiv.org/abs/2111.15378
Publikováno v:
2020 54th Asilomar Conference on Signals, Systems, and Computers
With the advances in virtual and augmented reality, gaming applications, and entertainment, certain indoor scenarios will require vastly higher capacity than what can be delivered by 5G. In this paper, we focus on massive MIMO for indoor environments
Externí odkaz:
http://arxiv.org/abs/2111.15339
A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation o
Externí odkaz:
http://arxiv.org/abs/2111.02709
Deep learning (DL) architectures have been successfully used in many applications including wireless systems. However, they have been shown to be susceptible to adversarial attacks. We analyze DL-based models for a regression problem in the context o
Externí odkaz:
http://arxiv.org/abs/2110.04731
The knowledge of channel covariance matrices is of paramount importance to the estimation of instantaneous channels and the design of beamforming vectors in multi-antenna systems. In practice, an abrupt change in channel covariance matrices may occur
Externí odkaz:
http://arxiv.org/abs/2109.04192
We study downlink (DL) channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in a time-division duplex. The users must know their effective channel gains to decode their received DL data signals. A common a
Externí odkaz:
http://arxiv.org/abs/2109.02463