2,866 research outputs found
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
Review of Recent Trends
This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe
Superimposed Signaling Inspired Channel Estimation in Full-Duplex Systems
Residual self-interference (SI) cancellation in the digital baseband is an important problem in full-duplex (FD) communication systems. In this paper, we propose a new technique for estimating the SI and communication channels in a FD communication system, which is inspired from superimposed signaling. In our proposed technique, we add a constant real number to each constellation point of a conventional modulation constellation to yield asymmetric shifted modulation constellations with respect to the origin. We show mathematically that such constellations can be used for bandwidth efficient channel estimation without ambiguity. We propose an expectation maximization (EM) estimator for use with the asymmetric shifted modulation constellations. We derive a closed-form lower bound for the mean square error (MSE) of the channel estimation error, which allows us to find the minimum shift energy needed for accurate channel estimation in a given FD communication system. The simulation results show that the proposed technique outperforms the data-aided channel estimation method, under the condition that the pilots use the same extra energy as the shift, both in terms of MSE of channel estimation error and bit error rate. The proposed technique is also robust to an increasing power of the SI signal
UNE PLATEFORME RADIO LOGICIELLE OUVERTE POUR LES SYSTÈMES 3G+
This paper describes a software-radio architecture developed for providing real-time wide-band radio communication capabilities in a form attractive for advanced 3G systems research. It is currently being used to implement signaling methods and protocols similar, but not limited to, evolving 3G radio standards (e.g. umts, cdma2000). An overview of the hardware system is provided along with example software implementations on both high-perfo-mance DSP systems and conventional microprocessor
Rate-Splitting to Mitigate Residual Transceiver Hardware Impairments in Massive MIMO Systems
Rate-Splitting (RS) has recently been shown to provide significant
performance benefits in various multi-user transmission scenarios. In parallel,
the huge degrees-of-freedom provided by the appealing massive Multiple-Input
Multiple-Output (MIMO) necessitate the employment of inexpensive hardware,
being more prone to hardware imperfections, in order to be a cost-efficient
technology. Hence, in this work, we focus on a realistic massive Multiple-Input
Single-Output (MISO) Broadcast Channel (BC) hampered by the inevitable hardware
impairments. We consider a general experimentally validated model of hardware
impairments, accounting for the presence of \textit{multiplicative distortion}
due to phase noise, \textit{additive distortion noise} and \textit{thermal
noise amplification}. Under both scenarios with perfect and imperfect channel
state information at the transmitter (CSIT), we analyze the potential
robustness of RS to each separate hardware imperfection. We analytically assess
the sum-rate degradation due to hardware imperfections. Interestingly, in the
case of imperfect CSIT, we demonstrate that RS is a robust strategy for
multiuser MIMO in the presence of phase and amplified thermal noise, since its
sum-rate does not saturate at high signal-to-noise ratio (SNR), contrary to
conventional techniques. On the other hand, the additive impairments always
lead to a sum-rate saturation at high SNR, even after the application of RS.
However, RS still enhances the performance. Furthermore, as the number of users
increases, the gains provided by RS decrease not only in ideal conditions, but
in practical conditions with RTHIs as well.Comment: accepted in IEEE TVT. arXiv admin note: text overlap with
arXiv:1702.0116
Towards joint communication and sensing (Chapter 4)
Localization of user equipment (UE) in mobile communication networks has been supported from the early stages of 3rd generation partnership project (3GPP). With 5th Generation (5G) and its target use cases, localization is increasingly gaining importance. Integrated sensing and localization in 6th Generation (6G) networks promise the introduction of more efficient networks and compelling applications to be developed
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