Connected living − the true vision of the Internet of Things (IoT) – offers improvement in the quality of life while presenting new business avenues. A combined effort by researchers, industries, manufacturers, service providers, and other stakeholders is required to address distinct IoT requirements. This convergence is expected to unleash a new dimension of opportunities that cannot be fully realized with conventional solutions. At the same time, 5G wireless promises a new connected ecosystem with potential technologies, like massive Multiple-Input and Multiple-Output (MIMO), Cloud Radio Access Network (C-RAN), Heterogeneous-CRAN (H-CRAN), mmWave, software-defined networking, information (content or data)-centric communication, Multi-RAT, and novel multiplexing. Since emerging 5G network is expected to revolutionize the way of communication, its design and standardization should consider IoT as one of the major guidelines. To this regard, we present technical details of emerging 5G networks inline with pressing IoT requirements, essential for the ultimate shaping of a connected living. We also delineate limitations of legacy networks to provide for peculiarities of IoT requirements.

The ever increasing proliferation of wireless objects and consistent connectivity demands are creating significant challenges for battery-constrained wireless devices. The vision of massive IoT, involving billions of smart objects to be connected to the cellular network, needs to address the problem of uninterrupted power consumption while taking advantage of emerging high-frequency 5G communications. The problem of limited battery power motivates us to utilize radio frequency (RF) signals as the energy source for battery-free communications in next-generation wireless networks. Backscatter communication (BackCom) makes it possible to harvest energy from incident RF signals and reflect back parts of the same signals while modulating the data. Ambient BackCom (Amb-BackCom) is a type of BackCom that can harvest energy from nearby WiFi, TV, and cellular RF signals to modulate information. The objective of this article is to review BackCom as a solution to the limited battery life problem and enable future battery-free communications for combating the energy issues for devices in emerging wireless networks. We first highlight the energy constraint in existing wireless communications. We then investigate BackCom as a practical solution to the limited battery life problem. Subsequently, in order to take the advantages of omnipresent radio waves, we elaborate BackCom tag architecture and various types of BackCom. To understand encoding and data extraction, we demonstrate signal processing aspects that cover channel coding, interference, decoding, and signal detection schemes. Moreover, we also describe BackCom communication modes, modulation schemes, and multiple access techniques to accommodate maximum users with high throughput. Similarly, to mitigate the increased network energy, adequate data and power transfer schemes for BackCom are elaborated, in addition to reliability, security, and range extension. Finally, we highlight BackCom applications with existing research challenges and future directions for next-generation 5G wireless networks.

Emerging mmWave enabled 5G wireless communications, offer tremendous increase in data demands and better quality expectations. However, high mmWave frequencies call for directional beamforming to overcome propagation limitations and enhance spatial capabilities. The establishment of new directional paradigm challenges the current Discontinuous Reception (DRX) mechanism for power saving in the User Equipment (UE). In this article, we introduce new Directional-Discontinuous Reception (DDRX) for directional air interface expected in mmWave enabled 5G communications. DDRX mechanism emphasizes the importance of beam searching for alignment of directional beams between UE and 5G base station (gNB), after every sleep cycle. Beam searching, though inevitable, reduces the effective sleep time. We propose three new DDRX mechanisms: Integrated DDRX (I-DDRX), Standalone DDRX (S-DDRX), and Cooperative DDRX (C-DDRX) to limit the impediments on power saving. Probabilistic estimation of UE's power saving and delay is performed for all the three different DDRX mechanisms using semi-Markov process. The power saving achieved in IDDRX is 12.1 percent higher than S-DDRX. The power saving of C-DDRX is 6.1 percent higher than S-DDRX. Analytical results of DDRX proposals are validated by simulation studies, performed over real wireless trace.

The rapid advancement in communication technological innovations results in proliferation of heterogeneous smart devices in the network. The inter-communication of these devices is usually related to their social behaviour and relationships. Furthermore, upcoming 5G network promises to bind all the network technologies like Internet of Vehicles (IoV), Internet of Things (IoT), Mobile Cloud Computing (MCC), Smart Grids (SG), Big Data, and Device-to-Device (D2D) communications in a common network. To achieve this unified goal, one promising possibility is to exploit social properties of various smart devices used by these technologies. Exploitation of social aspect can dispense optimized networking while avoiding problems like, network congestion, resource allocations, and the like. It also leads to convergence of upcoming 5G network technologies and human society giving rise to a new paradigm known as “socio-5G network technologies”. The state-of-the-art research on socio-5G network technologies is reviewed with the focus on six important technologies that 5G promises to support in one integrated network: IoV, IoT, MCC, SG, Big Data, and D2D communications. We also discuss the open issues related to combining social aspect with above-mentioned technologies.

Ever-increasing demand of data rate and subscriber penetration are resulting in continuous growth of mobile data traffic. In order to meet this exponential data traffic growth 3GPP Release 13, we have decided to enable the operation of Long Term Evolution (LTE) in the unlicensed band, termed as Licensed-Assisted Access (LAA). As the unlicensed spectrum is mainly used by WiFi, LTE evolved NodeB (eNB) has to perform Listen Before Talk (LBT) procedure to access the unlicensed channel. If the unlicensed spectrum is occupied by other services, User Equipment (UE) should remain active and wait for unlicensed channel to become idle. UE consumes a high power by remaining active, when unlicensed channel is not available. The UE's energy consumption could be saved by configuring Discontinuous Reception (DRX) in the unlicensed band, similar to DRX in LTE. In this article, we introduce and analyze a new Licensed-Assisted Access DRX mechanism (LAA-DRX) over LTE networks. Using our novel four state semi-Markov model, we show the probabilistic estimation of power saving and wake up latency associated with our proposed LAA-DRX process. Mathematical analysis and simulation results, using real wireless trace, point out that comparing to existing LTE DRX process, our LAA-DRX can achieve almost 4 percent higher power savings and up to 58 percent reduction in resource usage.

The expected rise of small devices in the Internet of Things (IoT) require these devices to operate without any power interruption. The replacement and recharging of batteries in these widely deployed small IoT devices is a challenging task. Recently, Ambient Backscatter Communications (AmB-Com) is introduced, which enables passive IoT devices to harvest power from nearby Radio Frequency (RF) signals. AmB-Com allows the passive devices to harvest energy and simultaneously transmit their information using the reflection of incident RF signals. This survey paper covers various types of ambient RF signals as the source of energy to energize passive IoT devices. Then, we show the utilization of multiple frequency bands to power up passive devices. In order to keep the balance between energy harvesting and information transfer, we discuss efficient power transfer schemes for AmB-Com in addition to energy management, resource allocation, and optimization techniques. Finally, we cover the performance of AmB-Com systems and highlight the research challenges in AmB-Com.