307 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
Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design
Massive multiple-input multiple-output (MIMO) systems are cellular networks
where the base stations (BSs) are equipped with unconventionally many antennas,
deployed on co-located or distributed arrays. Huge spatial degrees-of-freedom
are achieved by coherent processing over these massive arrays, which provide
strong signal gains, resilience to imperfect channel knowledge, and low
interference. This comes at the price of more infrastructure; the hardware cost
and circuit power consumption scale linearly/affinely with the number of BS
antennas . Hence, the key to cost-efficient deployment of large arrays is
low-cost antenna branches with low circuit power, in contrast to today's
conventional expensive and power-hungry BS antenna branches. Such low-cost
transceivers are prone to hardware imperfections, but it has been conjectured
that the huge degrees-of-freedom would bring robustness to such imperfections.
We prove this claim for a generalized uplink system with multiplicative
phase-drifts, additive distortion noise, and noise amplification. Specifically,
we derive closed-form expressions for the user rates and a scaling law that
shows how fast the hardware imperfections can increase with while
maintaining high rates. The connection between this scaling law and the power
consumption of different transceiver circuits is rigorously exemplified. This
reveals that one can make the circuit power increase as , instead of
linearly, by careful circuit-aware system design.Comment: Accepted for publication in IEEE Transactions on Wireless
Communications, 16 pages, 8 figures. The results can be reproduced using the
following Matlab code: https://github.com/emilbjornson/hardware-scaling-law
Degrees of Freedom of Time Correlated MISO Broadcast Channel with Delayed CSIT
We consider the time correlated multiple-input single-output (MISO) broadcast
channel where the transmitter has imperfect knowledge on the current channel
state, in addition to delayed channel state information. By representing the
quality of the current channel state information as P^-{\alpha} for the
signal-to-noise ratio P and some constant {\alpha} \geq 0, we characterize the
optimal degree of freedom region for this more general two-user MISO broadcast
correlated channel. The essential ingredients of the proposed scheme lie in the
quantization and multicasting of the overheard interferences, while
broadcasting new private messages. Our proposed scheme smoothly bridges between
the scheme recently proposed by Maddah-Ali and Tse with no current state
information and a simple zero-forcing beamforming with perfect current state
information.Comment: revised and final version, to appear in IEEE transactions on
Information Theor
Index Modulation Techniques for Energy-efficient Transmission in Large-scale MIMO Systems
This thesis exploits index modulation techniques to design energy- and spectrum-efficient system models to operate in future wireless networks. In this respect, index modulation techniques are studied considering two different media: mapping the information onto the frequency indices of multicarrier systems, and onto the antenna array indices of a platform that comprises multiple antennas.
The index modulation techniques in wideband communication scenarios considering orthogonal and generalized frequency division multiplexing systems are studied first. Single cell multiuser networks are considered while developing the system models that exploit the index modulation on the subcarriers of the multicarrier systems. Instead of actively modulating all the subcarriers, a subset is selected according to the index modulation bits. As a result, there are subcarriers that remain idle during the data transmission phase and the activation pattern of the subcarriers convey additional information.
The transceivers for the orthogonal and generalized frequency division multiplexing systems with index modulation are both designed considering the uplink and downlink transmission phases with a linear combiner and precoder in order to reduce the system complexity. In the developed system models, channel state information is required only at the base station. The linear combiner is designed adopting minimum mean square error method to mitigate the inter-user-interference. The proposed system models offer a flexible design as the parameters are independent of each other. The parameters can be adjusted to design the system in favor of the energy efficiency, spectrum efficiency, peak-to-average power ratio, or error performance.
Then, the index modulation techniques are studied for large-scale multiple-input multiple-output systems that operate in millimeter wave bands. In order to overcome the drawbacks of transmission in millimeter wave frequencies, channel properties should be taken in to account while envisaging the wireless communication network. The large-scale multiple-input multiple-output systems increase the degrees of freedom in the spatial domain. This feature can be exploited to focus the transmit power directly onto the intended receiver terminal to cope with the severe path-loss. However, scaling up the number of hardware elements results in excessive power consumption. Hybrid architectures provide a remedy by shifting a part of the signal processing to the analog domain. In this way, the number of bulky and high power consuming hardware elements can be reduced. However, there will be a performance degradation as a consequence of renouncing the fully digital signal processing. Index modulation techniques can be combined with the hybrid system architecture to compensate the loss in spectrum efficiency to further increase the data rates.
A user terminal architecture is designed that employs analog beamforming together with spatial modulation where a part of the information bits is mapped onto the indices of the antenna arrays. The system is comprised a switching stage that allocates the user terminal antennas on the phase shifter groups to minimize the spatial correlation, and a phase shifting stage that maximizes the beamforming gain to combat the path-loss. A computationally efficient optimization algorithm is developed to configure the system. The flexibility of the architecture enables optimization of the hybrid transceiver at any signal-to-noise ratio values.
A base station is designed in which hybrid beamforming together with spatial modulation is employed. The analog beamformer is designed to point the transmit beam only in the direction of the intended user terminal to mitigate leakage of the transmit power to other directions. The analog beamformer to transmit the signal is chosen based on the spatial modulation bits. The digital precoder is designed to eliminate the inter-user-interference by exploiting the zero-forcing method. The base station computes the hybrid beamformers and the digital combiners, and only feeds back the digital combiners of each antenna array-user pair to the related user terminals. Thus, a low complexity user architecture is sufficient to achieve a higher performance. The developed optimization framework for the energy efficiency jointly optimizes the number of served users and the total transmit power by utilizing the derived upper bound of the achievable rate. The proposed transceiver architectures provide a more energy-efficient system model compared to the hybrid systems in which the spatial modulation technique is not exploited.
This thesis develops low-complexity system models that operate in narrowband and wideband channel environments to meet the energy and spectrum efficiency demands of future wireless networks. It is corroborated in the thesis that adopting index modulation techniques both in the systems improves the system performance in various aspects.:1 Introduction 1
1.1 Motivation 1
1.2 Overview and Contribution 2
1.3 Outline 9
2 Preliminaries and Fundamentals 13
2.1 Multicarrier Systems 13
2.2 Large-scale Multiple Input Multiple Output Systems 17
2.3 Index Modulation Techniques 19
2.4 Single Cell Multiuser Networks 22
3 Multicarrier Systems with Index Modulation 27
3.1 Orthogonal Frequency Division Multiplexing 28
3.2 Generalized Frequency Division Multiplexing 40
3.3 Summary 52
4 Hybrid Beamforming with Spatial Modulation 55
4.1 Uplink Transmission 56
4.2 Downlink Transmission 74
4.3 Summary 106
5 Conclusion and Outlook 109
5.1 Conclusion 109
5.2 Outlook 111
A Quantization Error Derivations 113
B On the Achievable Rate of Gaussian Mixtures 115
B.1 The Conditional Density Function 115
B.2 Tight Bounds on the Differential Entropy 116
B.3 A Bound on the Achievable Rate 118
C Multiuser MIMO Downlink without Spatial Modulation 121
Bibliograph
Communications-Inspired Projection Design with Application to Compressive Sensing
We consider the recovery of an underlying signal x \in C^m based on
projection measurements of the form y=Mx+w, where y \in C^l and w is
measurement noise; we are interested in the case l < m. It is assumed that the
signal model p(x) is known, and w CN(w;0,S_w), for known S_W. The objective is
to design a projection matrix M \in C^(l x m) to maximize key
information-theoretic quantities with operational significance, including the
mutual information between the signal and the projections I(x;y) or the Renyi
entropy of the projections h_a(y) (Shannon entropy is a special case). By
capitalizing on explicit characterizations of the gradients of the information
measures with respect to the projections matrix, where we also partially extend
the well-known results of Palomar and Verdu from the mutual information to the
Renyi entropy domain, we unveil the key operations carried out by the optimal
projections designs: mode exposure and mode alignment. Experiments are
considered for the case of compressive sensing (CS) applied to imagery. In this
context, we provide a demonstration of the performance improvement possible
through the application of the novel projection designs in relation to
conventional ones, as well as justification for a fast online projections
design method with which state-of-the-art adaptive CS signal recovery is
achieved.Comment: 25 pages, 7 figures, parts of material published in IEEE ICASSP 2012,
submitted to SIIM
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