A Simulation Framework for Multiple-Antenna Terminals in 5G Massive MIMO Systems

Bengtsson, Erik; Rusek, Fredrik; Malkowsky, Steffen; Tufvesson, Fredrik; Karlsson, Peter; Edfors, Ove

doi:10.1109/access.2017.2775210

Cited by 39 publications

(23 citation statements)

References 14 publications

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“…MaMi has received a lot of attention in the wireless communication community [3]- [8] and suggests that capacity can be increased by an order of magnitude and energy-efficiency by two orders of magnitude. Except for a few papers [9]- [13], the terminal side of the MaMi system has not received much attention in the literature and relates mostly to idealized isotropically radiating single antenna terminals.…”

Section: Introductionmentioning

confidence: 99%

“…In [13] we proposed a cluster 1 based, link-level, MaMi simulation model that uses measured terminal-antenna characteristics. However, the scope of [13] was limited to a single terminal, although with multiple antennas, at a static physical location in space. It is, therefore, our ambition to extend the simulator, and this paper presents investigations of underlying channel properties that need to be accounted for.…”

Section: Introductionmentioning

confidence: 99%

“…It is, therefore, our ambition to extend the simulator, and this paper presents investigations of underlying channel properties that need to be accounted for. More specifically, in [20] the number of clusters is estimated using a channel sounder, but simplifications are made in [13] to include only clusters of significant power. This builds on the understanding that in the single-user (SU) case a zero-forcing erik.bengtsson@sony.com, jose.flordelis@eit.lth.se, fredrik.rusek@eit.lth.se peterc.karlsson@sony.com, fredrik.tufvesson@eit.lth.se, ove.edfors@eit.lth.se 1 Based on observations of wireless channels, [14]- [16] contributions of signals propagating along various paths, a.k.a.…”

Section: Introductionmentioning

confidence: 99%

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A Case Study on the Influence of Multiple Users on the Effective Channel in a Massive MIMO System

Bengtsson¹,

Flordelis

Rusek³

et al. 2020

IEEE Wireless Commun. Lett.

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We investigate the importance of weak clusters when modeling a wireless massive MIMO channel. We do this by studying the influence of densely spaced terminals and the number of base-station antennas for a zero-forcing precoded massive MIMO system. In particular, we focus on the influence on the correlation and imbalance between the signals at the terminal antennas, the effective channel-gain, the eigenvalue distributions and the number of clusters. The study is based on measured radiochannels from terminal prototypes with integrated antennas connected to a massive MIMO testbed. We further evaluate the advantage of using block-diagonalized zero-forcing compared to conventional zero-forcing in a massive MIMO system. Unexpectedly, terminals with low antenna envelope correlation coefficient may benefit significantly from block-diagonal zero-forcing in a massive MIMO system. The main conclusion is that weaker clusters are important when modeling multi-user scenarios.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Case Study on the Influence of Multiple Users on the Effective Channel in a Massive MIMO System

Bengtsson¹,

Flordelis

Rusek³

et al. 2020

IEEE Wireless Commun. Lett.

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“…MIMO antenna technologies are used in this system model, which applies a rank constraint scheme. MIMO has been extended to massive MIMO (MaMi) technologies involving hundreds of antennas . Channel parameters are measured to better utilize MIMO.…”

Section: Introductionmentioning

confidence: 99%

“…MIMO has been extended to massive MIMO (MaMi) technologies involving hundreds of antennas. 9 Channel parameters are measured to better utilize MIMO.…”

mentioning

confidence: 99%

Secure cognitive radio‐based synchronized transmission of 5G signals using massive MIMO‐OFDM‐ES

Pari

Karuppiah

Islam

2018

Int J Communication

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Summary A cognitive radio network (CRN) can address spectrum scarcity issues to achieve higher levels of spectral efficiency. Fifth‐generation (5G) technologies are advanced telecommunication technologies that are built into CRNs. Network performance is enhanced when using a massive multiple input multiple output (MIMO) system that tolerates a large number of users based on the use of multiple antennas. Several previous research works have been conducted on 5G CRNs, although these works have failed to mitigate interference and the peak‐to‐average power ratio (PAPR). In this paper, a 5G CRN with massive MIMO that ensures secure data transmission is developed. Security is ensured via the standardized key–based secrecy method supported by a certificate authority. A CRN fusion centre (FC) plays a vital role in decision making. Fusion centre rotation is applied to mitigate interference. Massive MIMO‐OFDM effective signalling is used to address PAPR problems. The proposed CRN is experimentally modelled using network simulator 3, and its performance is evaluated. Our simulation results reveal improvements in channel capacity, a reduction in the PAPR and bit error rates, and improvements in spectral efficiency.

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MassiveMIMOChannels

2020

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Massive MIMO (multiple‐input multiple‐output) is a fundamental technology in 5G systems. The characteristics of the radio channel experienced when operating with large antenna arrays differ from those of conventional multiple antenna systems. Hence, it is important to specifically characterize and model the underlying propagation channels with large antenna systems in mind. The channel models need to be realistic and accurate, but of low complexity, in order to be used to develop and assess the performance of future systems in a good way. This article gives an overview of state‐of‐the‐art of massive MIMO channels and related models. First, some fundamentals of massive MIMO propagation, including a comparison between micro‐wave and mm‐wave massive MIMO as well as the influence of user terminals, are provided. Then, channel characteristics that have been shown in measurements to be important in massive MIMO channels are presented. These include spherical wavefronts, nonstationarity, 3D propagation, and polarization effects. Further on, some channel‐dependent characteristics, which are experienced in massive MIMO systems, are in focus. In this article, we outline user separability and channel hardening, as an effect of favorable propagation conditions. Different channel modeling approaches are discussed, including the independent and identically distributed (i.i.d.) complex Gaussian channel model, correlation‐based channel models like the Kronecker and Weichselberger channel models, geometry‐based reference models, geometry‐based stochastic channel models (GSCMs), ray‐tracing and map‐based approaches. A brief overview of recently developed channel models, targeting massive MIMO channels, is also provided. Lastly, we discuss opportunities and challenges related to massive MIMO channels and modeling.

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A Simulation Framework for Multiple-Antenna Terminals in 5G Massive MIMO Systems

Cited by 39 publications

References 14 publications

A Case Study on the Influence of Multiple Users on the Effective Channel in a Massive MIMO System

A Case Study on the Influence of Multiple Users on the Effective Channel in a Massive MIMO System

Secure cognitive radio‐based synchronized transmission of 5G signals using massive MIMO‐OFDM‐ES

MassiveMIMOChannels

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