Recent Trends in Millimeter wave 5G Communication
Currently, the existing 4G network has reached its bandwidth bottleneck as the connected devices to internet is increasing rapidly. So we need new technology to handle high data traffic demand from multiple daily used electronics gadgets i.e, PDAs, other essential internet connected devices, and obviously to handle massive IoT devices, real time sensors, etc. which are becoming essential part of our life day by day. It is forecasted that 5G network will provide 1000 times more capacity than 4G network (Ahmed, 2018). Massive MIMO and millimetre wave band are the two main key ingredient to increase capacity in 5G network. Other technologies like, Device to Device communication (D2D), in-band full duplex (IBFD) will also contribute to improve capacity (Lin, 2019). Nowadays, most wireless technologies uses 300 MHz to 3 GHz but millimetre wave band ranges from 30 GHz to 300 GHz. Millimetre wave band along with massive MIMO will begin a new era of communication and will increase systems spectral efficiency (SE) (Ahmed, 2018). In spite of having high theoretical potential of enabling high data rate, millimetre wave band is easily absorbed by rain, wind etc. It also experiences foliage loss and high diffraction loss due to its much higher operating frequencies. Higher pathloss limits the range of radio link in the outdoor environment (Osseiran, 2016). So, the beamforming becomes essential to combat high pathloss. The mm wave band accommodated with a huge number of antenna elements over a small region at half-wavelength intervals. Massive MIMO system with large antenna array can provide narrow beams, so less interference. Other benefits of beamforming to achieve directivity, which increases the length of radio link. Recent research has focused on hybrid beamformig (combination of digital and analog beamforming) to overcome the limitation of analog and digital beamforming (Alkhateeb, 2014). A bigger portion of electricity bill of mobile operators come from its radio part, which is nearly 70% of total. So, nowadays we looking for energy efficient network. Hybrid beamforming is a great example of energy efficiency and less complex technique rather than digital beamforming technique (Ahmed, 2018). An analysis of developments and technologies for sparse precoding in mmWave Multiple input multiple output has been shown to enable hybrid beamforming is shown in. That research paper describes Spatially sparse HBF ( hybrid beamforming) can achieve performance near-optimal practical hybrid precoder (El Ayach, 2014). The fifth generation (5G) wireless network is suitable at solutions to overcome the bandwidth limitation, as well as other special features like extremely low latency, ubiquitous access, and fast data transmission rates. Spectral efficiency, extensions, and network densification are all solutions for achieving these objectives (Antonescu, 2017). It also observed that, nowadays monitoring of some infrastructures i.e., roads, industrial environments, ports, asset tracking, etc. becoming essential. On the other hand connected car has gained a great interest in recent era. So the machine type communication (MTC) is high demand to enable automation in different industries. The ultra-low latency property of millimetre wave band is very appropriate to quench the need of automation in industries (Osseiran, 2016). In case of vehicle to vehicle communication (V2V) or vehicle to infrastructure communication (V2I), owing to high mobility and the local-time varying radio channel, vehicular networks faces more complicated circumstances. Creating high gain beams in the mm-wave vehicular communication is especially difficult, as the beamforming procedures would be performed in a limited period of time. As a result, channel estimation becomes crucial. A position-assisted strategy that uses our adaptive channel estimation and previous positioning knowledge to speed up beamforming (Garcia, 2016). We can expect multi Gbps data communication enabling 5G millimetre wave communication in indoor environment. Ultra wide band and millimetre wave helps us to achieve the goal. Ultra wide band (UWB) are suitable for short range communication, i.e, indoor communication. UWB can allocate bandwidth of more than 500 MHz which is more than 20% of central frequency. The unlicensed 60 GHz millimetre wave is gaining more interests in commercial application, because of it can provide high data rates in short range communication, especially for indoor communication. 60 GHz band is easily absorbed by oxygen molecules. On the other hand we can achieve narrower beam using half wavelength spaced antenna elements in a small area. So, it can gives us less interference in case of device to device communication because of short range and narrower beam (Martinez, 2013). In case of UWB communication it transmits narrow impulses ranges upto picoseconds. That helps us to achieve positioning accuracy up to 5-10 centimetres. It can track the location of devices or objects in real time. On the other hand we allocate very low signal power that it cannot interface much with other signals of operating over those frequencies and obviously, it is suitable for short range communication (Frenzel, 2007). In case of, indoor communication channels industrial channel statistics show a significance difference between with compare to normal indoor communication. Now-a-days industrial machine to machine communication is growing interest rapidly (Traßl, 2019). For site-specific channel model, it do not operate well for other scenarios. Sometimes, it become costly to prepare channel model for everything, so ray tracing method is becoming so popular. In this method we can determine the channel parameter statistics by ray tracing. As millimetre wavelength is much shorter, so it acts like optical rays (Sidhu, 2012).
The exponential increase in wireless data traffic over the past few years has presented major challenges to the design and evolution of current wireless network architecture while simultaneously providing significant opportunities to innovate better future networks. The number of wireless devices are increasing day by day, but the fact is that the services by internet e.g, intelligent and self-driving, ultra-high definition video streaming and IoT devices or sensors requires not only high data rate communication but also ultra-low latency to operate in real time (Frenzel, 2007). Mobile data traffic will rise at a compound growth rate of 46 percent annually from 2011 to 2022. By 2022, it would have hit 2.58 exabytes (EBs) each day. Global internet protocol (IP) traffic is projected to exceed 4.8 zettabytes (ZBs) each year by 2022, according to statistics (Tiwari, 2019). Now a days, the LTE cellular system operates at Sub 6 GHz operating frequency with maximum bandwidth of 200 MHz. On the other hand WPAN which operates at 60 GHz unsilenced millimetre wave band can assign a bandwidth of 2 GHz to each channel (He, 2019). The millimetre wave band is considered as extremely high frequency ( or EHF) by ITU that covers a range of frequencies between 30 and 300 GHz. As its wavelength ranges from 1 millimetre to 10 millimetre, that’s why it’s called millimetre wave. Millimetre wave with massive MIMO will play a vital role in fulfilling these demands by offering high data rate wireless communication, where traffic from mobile and wireless devices will account for 71% of overall IP traffic. Mm-wave band has a great potential to enable high data rate communication unto 20 Gbps. Indian physicist Jagadish Chandra Bose first studied millimeter-length electromagnetic waves in the 1890s, and the earliest work on the mmWave frequency band can also be dated back to the 1890s by e.g. Bose and Lebedev (He, 2019). Major research activities have been dedicated to the investigation of mmWave networking for fifth-generation (5G) mobile networks in order to meet the different specifications of evolving traffic over the last few years. ITU has announced that the 3.4–3.6, 5.0–6.0, 24.25–28.35, 37–43.5, and 61–74 GHz bands would be made available for 5G connectivity in order to accommodate the exponential increase in mobile data traffic (He, 2019).
The number of MPCs available for communication for massive MIMO channels is limited which is much lower than the dimensions of the spatial channel. Due to high pathoss in atmosphere and poor scattering nature of millimeter wave, only few stronger MPCs are able to avail communication between Tx & Rx (Alkhateeb, 2014). Beamforming in millimeter wave band is required to combat high pathloss. Beamforming maximizes reception or transmission gain in a particular direction, minimizing in another direction. It significantly improves energy efficiency of system by focusing energy in a particular direction. Vehicular networks operate under more severe situations because of their high mobility (results doppler spread) & the radio channel's local-time varying existence, which greatly reduces the coherence time, etc (Garcia, 2016). Future autonomous safety and awareness applications for vehicles predict the requirement of up to 1 TB of data per hour of driving (Antonescu, 2017). Channel propagation models are basically two types, one is statistical model, and another is site-specific model. Most of the empirical or statistic models are suitable for specific applications. So it is needed to design a propagation model the can be deterministic and can be used to different environment without compromising accuracy much (Lin, 2019). Ray tracing model may be suitable for that because it is based on electromagnetic theory, and that calculates the reflecting and transmission power of EM wave using fresnel coefficient when signals (considered as ray because millimeter wave band wavelength is very short) are bounces of walls of buildings (Sidhu, 2018).