1,749 research outputs found
Towards a Realistic Assessment of Multiple Antenna HCNs: Residual Additive Transceiver Hardware Impairments and Channel Aging
Given the critical dependence of broadcast channels by the accuracy of
channel state information at the transmitter (CSIT), we develop a general
downlink model with zero-forcing (ZF) precoding, applied in realistic
heterogeneous cellular systems with multiple antenna base stations (BSs).
Specifically, we take into consideration imperfect CSIT due to pilot
contamination, channel aging due to users relative movement, and unavoidable
residual additive transceiver hardware impairments (RATHIs). Assuming that the
BSs are Poisson distributed, the main contributions focus on the derivations of
the upper bound of the coverage probability and the achievable user rate for
this general model. We show that both the coverage probability and the user
rate are dependent on the imperfect CSIT and RATHIs. More concretely, we
quantify the resultant performance loss of the network due to these effects. We
depict that the uplink RATHIs have equal impact, but the downlink transmit BS
distortion has a greater impact than the receive hardware impairment of the
user. Thus, the transmit BS hardware should be of better quality than user's
receive hardware. Furthermore, we characterise both the coverage probability
and user rate in terms of the time variation of the channel. It is shown that
both of them decrease with increasing user mobility, but after a specific value
of the normalised Doppler shift, they increase again. Actually, the time
variation, following the Jakes autocorrelation function, mirrors this effect on
coverage probability and user rate. Finally, we consider space division
multiple access (SDMA), single user beamforming (SU-BF), and baseline
single-input single-output (SISO) transmission. A comparison among these
schemes reveals that the coverage by means of SU-BF outperforms SDMA in terms
of coverage.Comment: accepted in IEEE TV
Massive MIMO for Crowd Scenarios: A Solution Based on Random Access
This paper presents a new approach to intra-cell pilot contamination in
crowded massive MIMO scenarios. The approach relies on two essential properties
of a massive MIMO system, namely near-orthogonality between user channels and
near-stability of channel powers. Signal processing techniques that take
advantage of these properties allow us to view a set of contaminated pilot
signals as a graph code on which iterative belief propagation can be performed.
This makes it possible to decontaminate pilot signals and increase the
throughput of the system. The proposed solution exhibits high performance with
large improvements over the conventional method. The improvements come at the
price of an increased error rate, although this effect is shown to decrease
significantly for increasing number of antennas at the base station
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
INTERFERENCE MANAGEMENT IN LTE SYSTEM AND BEYOUND
The key challenges to high throughput in cellular wireless communication system are interference, mobility and bandwidth limitation. Mobility has never been a problem until recently, bandwidth has been constantly improved upon through the evolutions in cellular wireless communication system but interference has been a constant limitation to any improvement that may have resulted from such evolution. The fundamental challenge to a system designer or a researcher is how to achieve high data rate in motion (high speed) in a cellular system that is intrinsically interference-limited.
Multi-antenna is the solution to data on the move and the capacity of multi-antenna system has been demonstrated to increase proportionally with increase in the number of antennas at both transmitter and receiver for point-to-point communications and multi-user environment. However, the capacity gain in both uplink and downlink is limited in a multi-user environment like cellular system by interference, the number of antennas at the base station, complexity and space constraint particularly for a mobile terminal.
This challenge in the downlink provided the motivation to investigate successive interference cancellation (SIC) as an interference management tool LTE system and beyond. The Simulation revealed that ordered successive interference (OSIC) out performs non-ordered successive interference cancellation (NSIC) and the additional complexity is justified based on the associated gain in BER performance of OSIC. The major drawback of OSIC is that it is not efficient in network environment employing power control or power allocation. Additional interference management techniques will be required to fully manage the interference.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format
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