The vision of next generation 5G wireless communications lies in providing very high data rates (typically of Gbps order), extremely low latency, manifold increase in base station capacity, and significant improvement in users' perceived quality of service (QoS), compared to current 4G LTE networks. Ever increasing proliferation of smart devices, introduction of new emerging multimedia applications, together with an exponential rise in wireless data (multimedia) demand and usage is already creating a significant burden on existing cellular networks. 5G wireless systems, with improved data rates, capacity, latency, and QoS are expected to be the panacea of most of the current cellular networks' problems. In this survey, we make an exhaustive review of wireless evolution toward 5G networks. We first discuss the new architectural changes associated with the radio access network (RAN) design, including air interfaces, smart antennas, cloud and heterogeneous RAN. Subsequently, we make an in-depth survey of underlying novel mm-wave physical layer technologies, encompassing new channel model estimation, directional antenna design, beamforming algorithms, and massive MIMO technologies. Next, the details of MAC layer protocols and multiplexing schemes needed to efficiently support this new physical layer are discussed. We also look into the killer applications, considered as the major driving force behind 5G. In order to understand the improved user experience, we provide highlights of new QoS, QoE, and SON features associated with the 5G evolution. For alleviating the increased network energy consumption and operating expenditure, we make a detail review on energy awareness and cost efficiency. As understanding the current status of 5G implementation is important for its eventual commercialization, we also discuss relevant field trials, drive tests, and simulation experiments. Finally, we point out major existing research issues and identify possible future research directions.

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.

Next generation 5G wireless networks envision innovative radio technologies for ultra dense deployment with improved coverage and higher data rates. However, the deployment of ultra dense 5G networks, with relatively smaller cells, raises significant challenges in network energy consumption. Emerging green cloud radio access networks (C-RANs) are providing assurance of energy efficient cellular operations for reduction of both greenhouse emissions and operators' energy bill. Cellular traffic dynamics play a significant role in efficient network energy management. In this paper, we first identify the complexity of the optimal traffic awareness in 5G C-RAN and design a framework for traffic-aware energy optimization. The virtual base station cluster (VBSC) of C-RAN exploits an information theoretic approach to model and analyze the uncertainty of cellular traffic, captured by remote radio heads (RRH). Subsequently, using an online, stochastic game theoretic algorithm, the VBS instances optimize and learn the cellular traffic patterns. Efficient learning makes the C-RAN aware of the near-future traffic. Traffic awareness helps in selective switching of a subset of RRHs, thus reducing the overall energy consumption. Our VBS prototype implementation, testbed experiments, and simulation results, performed with actual cellular traffic traces, demonstrate that our framework results in almost 25% daily energy savings and 35% increased energy efficiency with a negligible overhead.

The growth of IoT is expected to herald a better quality of life and open up new industrial opportunities. However, it is also raising new challenges in resource constrained wireless networks. Originally designed for human-to-human wireless communications, present wireless networks fail to satisfy the huge connectivity and varying traffic requirements of IoT. Next generation 5G wireless networks are expected to exploit emerging features, like mmWave, massive MIMO, and C-RAN, for providing the enormous connectivity, resource pooling, and energy efficiency required to support commercial rollout of IoT. Exploring these emerging features, we develop 5G-enabled IoT gateways to communicate with the RRHs of 5G C-RAN. The gateways are endowed with efficient compression schemes to significantly improve uplink resource utilization. Our 5G C-RAN prototyping and laboratory experimental results point out a huge opportunity for supporting a massive number of IoT-enabled devices by sophisticated 5G C-RAN deployment and efficient IoT gateway development.