143 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
Random Access Protocols for Massive MIMO
5G wireless networks are expected to support new services with stringent
requirements on data rates, latency and reliability. One novel feature is the
ability to serve a dense crowd of devices, calling for radically new ways of
accessing the network. This is the case in machine-type communications, but
also in urban environments and hotspots. In those use cases, the high number of
devices and the relatively short channel coherence interval do not allow
per-device allocation of orthogonal pilot sequences. This article motivates the
need for random access by the devices to pilot sequences used for channel
estimation, and shows that Massive MIMO is a main enabler to achieve fast
access with high data rates, and delay-tolerant access with different data rate
levels. Three pilot access protocols along with data transmission protocols are
described, fulfilling different requirements of 5G services
Grant-Free Massive MTC-Enabled Massive MIMO: A Compressive Sensing Approach
A key challenge of massive MTC (mMTC), is the joint detection of device
activity and decoding of data. The sparse characteristics of mMTC makes
compressed sensing (CS) approaches a promising solution to the device detection
problem. However, utilizing CS-based approaches for device detection along with
channel estimation, and using the acquired estimates for coherent data
transmission is suboptimal, especially when the goal is to convey only a few
bits of data.
First, we focus on the coherent transmission and demonstrate that it is
possible to obtain more accurate channel state information by combining
conventional estimators with CS-based techniques. Moreover, we illustrate that
even simple power control techniques can enhance the device detection
performance in mMTC setups.
Second, we devise a new non-coherent transmission scheme for mMTC and
specifically for grant-free random access. We design an algorithm that jointly
detects device activity along with embedded information bits. The approach
leverages elements from the approximate message passing (AMP) algorithm, and
exploits the structured sparsity introduced by the non-coherent transmission
scheme. Our analysis reveals that the proposed approach has superior
performance compared to application of the original AMP approach.Comment: Submitted to IEEE Transactions on Communication
Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks
The fifth generation of cellular communication systems is foreseen to enable
a multitude of new applications and use cases with very different requirements.
A new 5G multiservice air interface needs to enhance broadband performance as
well as provide new levels of reliability, latency and supported number of
users. In this paper we focus on the massive Machine Type Communications (mMTC)
service within a multi-service air interface. Specifically, we present an
overview of different physical and medium access techniques to address the
problem of a massive number of access attempts in mMTC and discuss the protocol
performance of these solutions in a common evaluation framework
Non-Coherent Active Device Identification for Massive Random Access
Massive Machine-Type Communications (mMTC) is a key service category in the
current generation of wireless networks featuring an extremely high density of
energy and resource-limited devices with sparse and sporadic activity patterns.
In order to enable random access in such mMTC networks, base station needs to
identify the active devices while operating within stringent access delay
constraints. In this paper, an energy efficient active device identification
protocol is proposed in which active devices transmit On-Off Keying (OOK)
modulated preambles jointly and base station employs non-coherent energy
detection avoiding channel estimation overheads. The minimum number of
channel-uses required by the active user identification protocol is
characterized in the asymptotic regime of total number of devices when
the number of active devices scales as along with an
achievability scheme relying on the equivalence of activity detection to a
group testing problem. Several practical schemes based on Belief Propagation
(BP) and Combinatorial Orthogonal Matching Pursuit (COMP) are also proposed.
Simulation results show that BP strategies outperform COMP significantly and
can operate close to the theoretical achievability bounds. In a
partial-recovery setting where few misdetections are allowed, BP continues to
perform well
Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years
Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions
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