Dirty RF: A New Paradigm

Fettweis, Gerhard; Löhning, Michael; Petrovic, D.; Windisch, Marcus; Zillmann, Peter; Rave, Wolfgang

doi:10.1007/s10776-006-0046-x

Cited by 145 publications

(119 citation statements)

References 31 publications

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“…This perhaps explains why transceiver impairments have received much less attention from the resource allocation community than other nonidealities such as CSI uncertainty and limited backhaul capacity. However, the degradations can be particularly severe in modern multi-cell systems using OFDM (which requires amplifiers with high dynamic range; see Remark 4.4), high-order modulations (which require high SINRs), low-cost equipment (which are relatively non-ideal), and transmit-side interference mitigation (which needs accurate CSI and channel models) [72,94,255].…”

Section: Transceiver Impairmentsmentioning

confidence: 99%

Optimal Resource Allocation in Coordinated Multi-Cell Systems

Björnson

2013

FNT in Communications and Information Theory

298

317

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The use of multiple antennas at base stations is a key component in the design of cellular communication systems that can meet high-capacity demands in the downlink. Under ideal conditions, the gain of employing multiple antennas is well-recognized: the data throughput increases linearly with the number of transmit antennas if the spatial dimension is utilized to serve many users in parallel. The practical performance of multi-cell systems is, however, limited by a variety of nonidealities, such as insufficient channel knowledge, high computational complexity, heterogeneous user conditions, limited backhaul capacity, transceiver impairments, and the constrained level of coordination between base stations. This tutorial presents a general framework for modeling different multi-cell scenarios, including clustered joint transmission, coordinated beamforming, interference channels, cognitive radio, and spectrum sharing between operators. The framework enables joint analysis and insights that are both scenario independent and dependent.The performance of multi-cell systems depends on the resource allocation; that is, how the time, power, frequency, and spatial resources are divided among users. A comprehensive characterization of resource allocation problem categories is provided, along with the signal processing algorithms that solve them. The inherent difficulties are revealed: (a) the overwhelming spatial degrees-of-freedom created by the multitude of transmit antennas; and (b) the fundamental tradeoff between maximizing aggregate system throughput and maintaining user fairness. The tutorial provides a pragmatic foundation for resource allocation where the system utility metric can be selected to achieve practical feasibility. The structure of optimal resource allocation is also derived, in terms of beamforming parameterizations and optimal operating points.This tutorial provides a solid ground and understanding for optimization of practical multi-cell systems, including the impact of the nonidealities mentioned above. The Matlab code is available online for some of the examples and algorithms in this tutorial. IntroductionThis section describes a general framework for modeling different types of multi-cell systems and measuring their performance -both in terms of system utility and individual user performance. The framework is based on the concept of dynamic cooperation clusters, which enables unified analysis of everything from interference channels and cognitive radio to cellular networks with global joint transmission. The concept of resource allocation is defined as allocating transmit power among users and spatial directions, while satisfying a set of power constraints that have physical, regulatory, and economic implications. A major complication in resource allocation is the inter-user interference that arises and limits the performance when multiple users are served in parallel. Resource allocation is particularly complex when multiple antennas are employed at each base station. However, the throu...

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Section: Transceiver Impairmentsmentioning

confidence: 99%

Optimal Resource Allocation in Coordinated Multi-Cell Systems

Björnson

2013

FNT in Communications and Information Theory

298

317

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“…As in the transmission performance in wireless systems, the measurement accuracy of channel sounders is degraded due to various hardware imperfections such as ADCs'/DACs' skew and amplitude mismatch [51], RF transceiver's I/Q mismatch, carrier leakage [52]- [54], and nonlinearity [51], LO's phase noise, frequency error [51], [55], etc. Since the channel sounder has fully parallel transceiver architecture, a precise calibration is needed for accurate multidimensional high-resolution channel measurement.…”

Section: Calibrationmentioning

confidence: 99%

Multi-Dimensional Radio Channel Measurement, Analysis and Modeling for High Frequency Bands

Kim

Takada

Saito

2018

IEICE Trans. Commun.

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SUMMARY In order to utilize higher frequency bands above 6 GHz, which is an important technical challenge in fifth generation mobile systems, radio propagation channel properties in a large variety of deployment scenarios should be thoroughly investigated. The authors' group has been involved in a fundamental research project aimed at investigating multipleinput-multiple-output (MIMO) transmission performance and propagation channel properties at microwave frequency above 10 GHz from 2009 to 2013, and since then they have been conducting measurement and modeling for high frequency bands. This paper aims at providing comprehensive tutorial of a whole procedure of channel modeling; multi-dimensional channel sounding, propagation channel measurement, analysis, and modeling, by introducing the developed MIMO channel sounders at high frequency bands of 11 and 60 GHz and presenting some measurement results in a microcell environment at 11 GHz. Furthermore, this paper identifies challenges in radio propagation measurements, and discusses current/future channel modeling issues as future works.

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“…This is related to the dirty RF paradigm where the analog components are designed based on some suitable criterion (e.g., high energy-efficiency or small chip area), while nonidealities are compensated by digital signal processing techniques [5,72]. These techniques cannot remove the distortions completely, but the residual distortions are well-modeled as additive Gaussian noise with a variance that increases with the power of the transmitted signal.…”

Section: Transceiver Impairmentsmentioning

confidence: 99%