This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.

Spatially Sparse Precoding in Millimeter Wave MIMO Systems

Millimeter-wave (mmW) frequencies between 30 and 300 GHz are a new frontier for cellular communication that offers the promise of orders of magnitude greater bandwidths combined with further gains via beamforming and spatial multiplexing from multielement antenna arrays. This paper surveys measurements and capacity studies to assess this technology with a focus on small cell deployments in urban environments. The conclusions are extremely encouraging; measurements in New York City at 28 and 73 GHz demonstrate that, even in an urban canyon environment, significant non-line-of-sight (NLOS) outdoor, street-level coverage is possible up to approximately 200 m from a potential low-power microcell or picocell base station. In addition, based on statistical channel models from these measurements, it is shown that mmW systems can offer more than an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks at current cell densities. Cellular systems, however, will need to be significantly redesigned to fully achieve these gains. Specifically, the requirement of highly directional and adaptive transmissions, directional isolation between links, and significant possibilities of outage have strong implications on multiple access, channel structure, synchronization, and receiver design. To address these challenges, the paper discusses how various technologies including adaptive beamforming, multihop relaying, heterogeneous network architectures, and carrier aggregation can be leveraged in the mmW context.

Millimeter-Wave Cellular Wireless Networks: Potentials and Challenges

Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e., multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this correspondence, a system where each receiver has perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well-known zero-forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite-rate feedback are derived. A key finding is that the feedback rate per mobile must be increased linearly with the signal-to-noise ratio (SNR) (in decibels) in order to achieve the full multiplexing gain. This is in sharp contrast to point-to-point multiple-input multiple-output (MIMO) systems, in which it is not necessary to increase the feedback rate as a function of the SNR

MIMO Broadcast Channels With Finite-Rate Feedback

There is considerable pressure to define the key requirements of 5G, develop 5G standards, and perform technology trials as quickly as possible. Normally, these activities are best done in series but there is a desire to complete these tasks in parallel so that commercial deployments of 5G can begin by 2020. 5G will not be an incremental improvement over its predecessors; it aims to be a revolutionary leap forward in terms of data rates, latency, massive connectivity, network reliability, and energy efficiency. These capabilities are targeted at realizing high-speed connectivity, the Internet of Things, augmented virtual reality, the tactile internet, and so on. The requirements of 5G are expected to be met by new spectrum in the microwave bands (3.3-4.2 GHz), and utilizing large bandwidths available in mm-wave bands, increasing spatial degrees of freedom via large antenna arrays and 3-D MIMO, network densification, and new waveforms that provide scalability and flexibility to meet the varying demands of 5G services. Unlike the one size fits all 4G core networks, the 5G core network must be flexible and adaptable and is expected to simultaneously provide optimized support for the diverse 5G use case categories. In this paper, we provide an overview of 5G research, standardization trials, and deployment challenges. Due to the enormous scope of 5G systems, it is necessary to provide some direction in a tutorial article, and in this overview, the focus is largely user centric, rather than device centric. In addition to surveying the state of play in the area, we identify leading technologies, evaluating their strengths and weaknesses, and outline the key challenges ahead, with research test beds delivering promising performance but pre-commercial trials lagging behind the desired 5G targets.

5G : A tutorial overview of standards, trials, challenges, deployment, and practice

A method for communicating control channel information in a wireless communication system, including transmitting a super-frame having a time-frequency resource region containing an allocation control channel and multiple pilot elements, at least some of which are associated with the allocation control channel, and indicating, in a configuration information control channel of the super-frame, a characteristic of the pilots elements associated with the allocation control channel.

Hierarchical pilot structure in wireless communication systems

A communication system based upon frequency-domain MIMO processing is disclosed. A transmitting device of the communication system transforms time-domain signals into frequency-domain signals, and weights each frequency-domain signal to form weighted frequency-domain signals with each weighted frequency-domain signal being a function of each frequency-domain signal. The transmitting device transmits weighted time-domain waveforms as a function of the weighted frequency-domain signals. In response thereto, a receiving device of the communication system provides frequency-domain samples that are a function of the one or more weighted time-domain waveforms and weights each frequency-domain sample to form one or more weighted frequency-domain samples with each weighted frequency-domain sample being a function of each frequency-domain sample. The receiving device decodes the weighted frequency-domain sample to obtain the information represented by the time-domain signals.

Frequency-domain MIMO processing method and system

A receiving device and method for operating a communication system are provided. The receiving device receives a plurality of time-domain Doppler channel estimates for at least one transmitter, a plurality of Doppler sinusoids, and a spatial covariance matrix of a corrupting environment. A Doppler spatial covariance matrix is created as a function of the time-domain Doppler channel estimates and the Doppler sinusoids. A total Doppler spatial covariance matrix is created as a function of the spatial covariance matrix of the corrupting environment and the Doppler spatial covariance matrix. A Doppler steering vector is created for at least one transmitter as a function of the Doppler channel estimates and the Doppler sinusoids. A combining weight for the at least one transmitter is then created as a function of the total Doppler spatial covariance matrix and the Doppler steering vector for at least one transmitter.

Method and device for adaptive antenna combining weights

A receiving device and method for operating a communication system are provided. The receiving device receives at least one Doppler channel estimate for at least one transmitter and a spatial covariance matrix of a corrupting environment. The Doppler channel estimates are used to create a Null Doppler spatial covariance matrix. A total Doppler spatial covariance matrix is created as a sum of the spatial covariance matrix of the corrupting environment, plus the Doppler spatial covariance matrix. A combining weight for at least one transmitter and at least one Doppler channel is created from the total Doppler spatial covariance and the at least one Doppler channel for the at least one transmitter.

Method and device for fixed in time adaptive antenna combining weights

The invention is a method of estimating the time and frequency response of at least one desired signal received by at least one antenna, based on Gradient Optimization techniques. Through the use of gradient optimization techniques and efficient DFT processing, the invention provides frequency response estimates that require fewer computations than prior art decision-directed channel estimation devices.

Timothy A. Thomas

Papers

Hierarchical pilot structure in wireless communication systems

Frequency-domain MIMO processing method and system

Method and device for adaptive antenna combining weights

Method and device for fixed in time adaptive antenna combining weights

Method and device for multi-user frequency-domain channel estimation based on gradient optimization techniques