5,989 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
Cooperative diversity using MIMO systems
Multipath fading is one of the primary factors for degrading the performance in a wireless network. Information theoretic and past research suggest the use various diversity techniques to combat fading in wireless networks. Antenna diversity, a form of diversity technique, when incorporated in a wireless transceiver increases the system capacity and is one of the effective methods to combat fading in wireless systems. Also, recent research by Laneman et.al., Sendonaris et.al. suggests that cooperation among users in a wireless networks is an effective approach for a better signal reception in multipath fading environments. The diversity gains obtained by cooperation among the users of a wireless network is termed as cooperative diversity . Although, prior research in cooperative diversity considers users equipped with single antenna, in practical scenarios users may be able to accommodate multiple antennas due to the recent advanced research in semiconductor industry. Hence, the primary purpose of this thesis is to design, simulate and analyze an end-end performance of multi-antenna wireless systems employing cooperative multi antenna relay nodes so as to exploit the cooperative diversity and antenna diversity simultaneously in a wireless networks. Three main contributions to the area of cooperative multiple-input multiple-output (MIMO) wireless systems is presented in this thesis. First, we perform information theoretic analysis to study the impact of antenna arrays on cooperative wireless networks and propose the best possible distribution of antenna arrays among the three terminals of a simple three terminal cooperative relay network. Second, we design, simulate, and analyze a cooperative multiple-input multiple-output (MIMO) wireless systems employing orthogonal space-time block codes as proposed by Alamouti in 1998 with a decode-and-forward (DF) relay terminal. We implement a maximal ratio combining receiver that provides almost twice the diversity gain with respect to point-point multiple input multiple output link. Finally, we implement a practical receiver for cooperative reception using multiple antennas at all nodes based on Bell-Labs Layered Space Time architecture (BLAST). We incorporate a practical adaptive decode-and-forward (DF) relaying technique for reliable signal retransmission for both Alamouti space-time coding and the BLAST schemes. Results presented in terms of bit error rates and throughput show that remarkable performance gains are achievable by combining the concepts drawn from space-time coding, cooperative relaying and array processing
A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles
In recent years, there has been a dramatic increase in the use of unmanned
aerial vehicles (UAVs), particularly for small UAVs, due to their affordable
prices, ease of availability, and ease of operability. Existing and future
applications of UAVs include remote surveillance and monitoring, relief
operations, package delivery, and communication backhaul infrastructure.
Additionally, UAVs are envisioned as an important component of 5G wireless
technology and beyond. The unique application scenarios for UAVs necessitate
accurate air-to-ground (AG) propagation channel models for designing and
evaluating UAV communication links for control/non-payload as well as payload
data transmissions. These AG propagation models have not been investigated in
detail when compared to terrestrial propagation models. In this paper, a
comprehensive survey is provided on available AG channel measurement campaigns,
large and small scale fading channel models, their limitations, and future
research directions for UAV communication scenarios
Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
This paper surveys recent advances in the area of very large MIMO systems.
With very large MIMO, we think of systems that use antenna arrays with an
order of magnitude more elements than in systems being built today, say a
hundred antennas or more. Very large MIMO entails an unprecedented number of
antennas simultaneously serving a much smaller number of terminals. The
disparity in number emerges as a desirable operating condition and a practical
one as well. The number of terminals that can be simultaneously served is
limited, not by the number of antennas, but rather by our inability to acquire
channel-state information for an unlimited number of terminals. Larger numbers
of terminals can always be accommodated by combining very large MIMO technology
with conventional time- and frequency-division multiplexing via OFDM. Very
large MIMO arrays is a new research field both in communication theory,
propagation, and electronics and represents a paradigm shift in the way of
thinking both with regards to theory, systems and implementation. The ultimate
vision of very large MIMO systems is that the antenna array would consist of
small active antenna units, plugged into an (optical) fieldbus.Comment: Accepted for publication in the IEEE Signal Processing Magazine,
October 201
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Space-time-frequency methods for interference-limited communication systems
textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin
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