Physical Layer of Wireless IoT: Enablers and Issues

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Penn State

The current trend in telecommunications market is towards connecting all the everyday useful objects to the Internet. In this direction, Internet of Things (IoT) is receiving significant attention from industries and research communities as a key enabler for the Fifth Generation (5G) of wireless communications. It is about connecting all types of physical things/objects/devices to the Internet. The term IoT is also referred as Internet of Everything (IoE), which basically brings people, data, things and processes together in order to fulfil everyday needs of people, thus enabling a smart global community.  Among numerous application areas of IoT, some of the important ones are: (i) smart home, (ii) smart cities, (iii) smart wearables, (iv) smart grids, (v) smart healthcare, (vi) connected car, (vii) remote industrial process control, (viii) smart retail and supply chain, (ix) smart farming, and (x) smart energy management.

According to CISCO, IoT was initiated sometime between 2008 and 2009 when the number of connected devices exceeded the number of people. Several new devices having different form factors and enhanced capabilities/intelligence are emerging each year in the market. It has been forecasted that there will be around 8.2 billion handheld or personal mobile-ready devices and 3.2 billion Machine to Machine (M2M) connections by 2020. Based on CISCO whitepaper 2016, another important evolution is the massive emergence of smart wearable devices which may reach around 601 million globally by 2020, growing at the cumulative aggregated growth rate of 44 percentage. Furthermore, the ongoing trend of migrating to IPV6 with its 340 undecillion addresses will facilitate the integration of smart devices in the future wireless networks, thus making the market place and the concept of IoE feasible. Although there are other possibilities for communication between IoT devices such as Ethernet connectivity, Fieldbus and power line communication, this blog focuses on physical layer enablers and issues for wireless connectivity among IoT devices.

IoT will potentially create the integration of different wireless technologies, and subsequently will create market for new services. Some of the existing PHY layer protocols related to wireless IoT are IEEE 802.15.4, IEEE 802.15.6, Bluetooth Low Energy (BLE), EPCglobal, LTE-A, Z-Wave, 6LowPAN, and Near Field Communication (NFC). Future 5G networks may need to ensure the rapidly emerging requirements of IoT applications. Some relevant Quality of Service (QoS) requirements include spectral efficiency, energy efficiency, connectivity and latency. To meet these diverse requirements, an efficient, scalable and flexible air-interface is required and, therefore, different modules of Physical (PHY) and Medium Access Control (MAC) layers should be optimized so that they can be configured flexibly according to the technical specifications of each use case. One of the important aspects in this regard is the design of PHY layer for IoT-based wireless systems considering the practical constraints of energy efficiency, spectral efficiency, cost-effectiveness, and quality of experience.

However, the design of IoT-enabled wireless networks which can deliver a variety of services with desirable quality of experience under energy/resource constrained practical wireless scenarios is crucial. In contrast to other wireless communication paradigms, IoT has its own unique features and diverse requirements such as group-based communication, time-tolerant, small data transmission, secure connection, monitoring surrounding environment/parameters, low cost and low energy consumption. Besides, several requirements such as bandwidth, reliability and latency of different existing services are highly diverse. In terms of connectivity, it’s challenging to find out which devices need to be connected and which communication technology is suitable to connect them. Furthermore, several other issues such as dynamic resource allocation, harmful interference mitigation and interoperability of different technologies have to be investigated while devising communication technologies for IoT.

The PHY layer parameters should be effectively utilized in devising MAC layer and network layer protocols in order to design end to end reliable communication systems. The key enabling PHY layer techniques for wireless IoT are dynamic resource allocation (carrier and power), distributed beamforming/space time block code, opportunistic/cognitive techniques, orthogonal/non-orthogonal multiple access, low complexity cooperative techniques, compressive signal processing, spectrum sensing techniques, energy efficient modulation design, RF energy harvesting techniques, adaptive waveforms, and mmWave technologies. Furthermore, there are several emerging application areas of wireless IoT such as Wireless Body Area Networks (WBANs), Wireless Sensor Networks (WSNs), Device to Device (D2D), Machine to Machine (M2M), Vehicle to Vehicle (V2V), Vehicular Ad Hoc Networks (VANETs) satellite communications, LTE-advanced and 5G networks. These wireless systems have their own specific characteristics and it’s crucial to understand their PHY layer characteristics in order to deploy a reliable end to end system.

A massive amount of IoT devices may need to be fabricated in a cost effective manner. Furthermore, these devices are likely to be battery operated and located in a remote area where charging may be economically infeasible. On the other hand, IoT devices may likely be miniaturized in size and non-replaceable. This implies that cost, energy, network lifetime and space efficiency will be the critical challenges of the future IoT devices. In this regard, suitable signal processing tools from various areas such as WSNs and radar can be adopted for IoT-based wireless systems.

Future IoT enabled wireless systems require a highly scalable, reliable and available radio spectrum. The existing static spectrum allocation mechanisms which are mainly based on orthogonalization of the spectrum resources may not be viable solutions. In this regard, dynamic and non-orthogonal spectrum allocation policies are promising. One possible direction could be to allow the IoT devices to simultaneously utilize both microwave and mmWave carrier frequency bands (i.e., dual band connectivity). On the other hand, in order to support wideband IoT applications, both contiguous and non-contiguous carrier aggregation may be employed especially at the microwave frequency bands. In this context, the main challenge is how to efficiently realize wideband IoT capable of simultaneously utilizing the benefits of microwave and mmWave frequency bands.

While considering wideband spectrum utilization for IoT applications, the conventional Nyquist-based sampling is not feasible due to the requirements of very high rate and expensive ADC. In this regard, it would be interesting to exploit the inherent time, frequency sparsity caused by sporadic traffic of IoT-based systems as well as the spatial sparsity exhibited due to multipath environment, and subsequently to apply compressive signal processing in order to devise efficient techniques such as wideband sensing and channel estimation.

IoT being a complex paradigm, it faces several technical challenges in wireless communications which need to be addressed with further research and development activities. More specifically, future research efforts may need to focus in designing low cost and energy efficient transceiver and incorporating PHY layer parameters in the design of MAC and network layers to realize reliable IoT-based wireless systems.

Shree Krishna Sharma
Tadilo Endeshaw Bogale
Danda B. Rawat

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