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Time-domain Channel Property Feedback in 5G-Advanced and Beyond
Authors:
Per Ernström,
Siva D. Muruganathan,
Keerthi Kumar Nagalapur,
Fredrik Athley
Abstract:
The availability of time-variability information of a channel between a network node and a user equipment at the network side allows a 5G network to optimally configure its parameters to maximize both user and system performance. In the Release 18 enhancements of 5G-Advanced, a time-domain channel property (TDCP) feedback that indicates the degree of time-variability of the channel is being standa…
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The availability of time-variability information of a channel between a network node and a user equipment at the network side allows a 5G network to optimally configure its parameters to maximize both user and system performance. In the Release 18 enhancements of 5G-Advanced, a time-domain channel property (TDCP) feedback that indicates the degree of time-variability of the channel is being standardized. In this article, we describe the standardized TDCP feedback and its applications. The benefit of the feedback is further illustrated through numerical evaluations.
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Submitted 26 July, 2023;
originally announced July 2023.
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Analysis of Massive MIMO With Hardware Impairments and Different Channel Models
Authors:
Fredrik Athley,
Giuseppe Durisi,
Ulf Gustavsson
Abstract:
Massive Multiple-Input Multiple-Output (MIMO) is foreseen to be one of the main technology components in next generation cellular communications (5G). In this paper, fundamental limits on the performance of downlink massive MIMO systems are investigated by means of simulations and analytical analysis. Signal-to-noise-and-interference ratio (SINR) and sum rate for a single-cell scenario multi-user…
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Massive Multiple-Input Multiple-Output (MIMO) is foreseen to be one of the main technology components in next generation cellular communications (5G). In this paper, fundamental limits on the performance of downlink massive MIMO systems are investigated by means of simulations and analytical analysis. Signal-to-noise-and-interference ratio (SINR) and sum rate for a single-cell scenario multi-user MIMO are analyzed for different array sizes, channel models, and precoding schemes. The impact of hardware impairments on performance is also investigated. Simple approximations are derived that show explicitly how the number of antennas, number of served users, transmit power, and magnitude of hardware impairments affect performance.
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Submitted 17 January, 2015;
originally announced January 2015.
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On the Impact of Hardware Impairments on Massive MIMO
Authors:
Ulf Gustavsson,
Cesar Sanchéz-Perez,
Thomas Eriksson,
Fredrik Athley,
Giuseppe Durisi,
Per Landin,
Katharina Hausmair,
Christian Fager,
Lars Svensson
Abstract:
Massive multi-user (MU) multiple-input multiple-output (MIMO) systems are one possible key technology for next generation wireless communication systems. Claims have been made that massive MU-MIMO will increase both the radiated energy efficiency as well as the sum-rate capacity by orders of magnitude, because of the high transmit directivity. However, due to the very large number of transceivers…
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Massive multi-user (MU) multiple-input multiple-output (MIMO) systems are one possible key technology for next generation wireless communication systems. Claims have been made that massive MU-MIMO will increase both the radiated energy efficiency as well as the sum-rate capacity by orders of magnitude, because of the high transmit directivity. However, due to the very large number of transceivers needed at each base-station (BS), a successful implementation of massive MU-MIMO will be contingent on of the availability of very cheap, compact and power-efficient radio and digital-processing hardware. This may in turn impair the quality of the modulated radio frequency (RF) signal due to an increased amount of power-amplifier distortion, phase-noise, and quantization noise.
In this paper, we examine the effects of hardware impairments on a massive MU-MIMO single-cell system by means of theory and simulation. The simulations are performed using simplified, well-established statistical hardware impairment models as well as more sophisticated and realistic models based upon measurements and electromagnetic antenna array simulations.
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Submitted 26 November, 2014;
originally announced November 2014.