Fading Channels: InformationTheoretic and Communications Aspects

By Sergio VerdÂ, Steven W. McLaughlin. 2000

685 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Deep Learning for Distributed Optimization: Applications to Wireless Resource Management (2019, background): “, the ergodic capacity and the average power consumption [25].”
Constrained Deep Learning for Wireless Resource Management (2019, background): “, the ergodic capacity and the average power consumption [12].”
How much training is needed in multiple-antenna wireless links? (2003, background): “The true channel capacity, however, (which does not necessarily require training to achieve) decays as , rather than as [17], [18].”
Fading relay channels: performance limits and space-time signal design (2004, background): “In this case, we resort to the % outage capacity [27], [28], , defined as”
Cooperative diversity in wireless networks: algorithms and architectures (2002, background): “-outage/outage probability [59, 12] or delay-limited capacity [34] can be employed to evaluate the efficacy of multiantenna schemes.”
Dynamic association for load balancing and interference avoidance in multi-cell networks (2007, background): “Moreover, equal power allocation is near optimal in many cases especially in high SINR regime [15]–[17].”
Unitary space-time modulation for multiple-antenna communications in Rayleigh flat fading (2000, background): “Its effects are often mitigated by some combination of differen tial phase modulation, interleaving, or the transmission of pilot or training signals [1].”
Relaying Protocols for Wireless Energy Harvesting and Information Processing (2012, background): “Thus, it is possible to achieve the ergodic capacity by transmitting at a rate equal to the ergodic capacity without any rate adaptation or requiring any knowledge about the channel state information at the source or the relay node [22].”
RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks (2019, background): “, the probability that the Shannon capacity falls below the transmission rate R [56].”
The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel (2000, background): “If the distribution is not known, then mismatch issues [6] must be considered.”
Towards an information theory of large networks: an achievable rate region (2001, methodology): “values from block to block [6], [18], [26].”
Dynamic Resource Allocation in Cognitive Radio Networks (2010, background): “Note that DRA for traditional (non-CR) wireless networks under PTPC and/or ATPC has been thoroughly studied in the literature [12], while the study of DRA subject to PIPC and/or AIPC as well as their various combinations with PTPC/ATPC is unique to CR networks and is relatively new.”
Design, analysis, and performance evaluation for BICM-ID with square QAM constellations in Rayleigh fading channels (2001, background): “This technique is also known as signal spaceor modulationdiversity [8], [9] and shows significant improvement for uncoded systems [8], [10] as well as for TCM [11], [10] on Rayleigh fading channels.”
Scalable Cell-Free Massive MIMO Systems (2019, methodology): “The ergodic capacity is unknown for this setup, but we can rigorously analyze the performance by using standard capacity lower bounds [2], [46], which we refer to as achievable SEs.”