Improved mobile device battery lifetime and latency minimization are critical requirements for enhancing the mobile broadband services and user experience. Long-term evolution (LTE) networks have adopted discontinuous reception (DRX) as the baseline solution for prolonged battery lifetime. However, in every DRX cycle, the mobile device baseband processing unit monitors and decodes the control signaling, and thus, all instances without any actual data allocation leads to unnecessary energy consumption. This fact together with the long start-up and power-down times can prevent adopting frequent wake-up instants, which, in turn, leads to considerable latency. In this work, a novel wake-up scheme is described and studied, to tackle the trade-off between latency and battery lifetime in future 5G networks, seeking thus to facilitate an always-available experience, rather than always-on. Analytical and simulation-based results show that the proposed scheme is a promising approach to control the user plane latency and energy consumption, when the device is operating in the power saving mode. The aim of this article is to describe the overall wake-up system operating principle and the associated signaling methods, receiver processing solutions and essential implementation aspects. Additionally, the advantages compared to DRX-based systems are shown and demonstrated, through the analysis of the system energy-efficiency and latency characteristics, with special emphasis on future 5G-grade mobile devices.

Recently, wake-up scheme has been proposed to enhance the energy-efficiency of 5G mobile devices and prolong its battery lifetime while reducing the buffering delay. The existing wake-up optimization mechanisms use off-line methods and are tied to specific traffic models. In this paper, a novel concept of wake-up scheduling is introduced to further improve the energy-efficiency of mobile devices and to deal with realistic traffic. The main idea is to use a fixed configuration of the wake-up scheme and adjust the scheduling of the wake-up signals dynamically. For this, a proactive wake-up scheduler is proposed to take online decisions based on traffic prediction. Towards this end, a framework to predict packet arrivals based on recurrent neural networks is developed. Numerical results show that for given delay requirements of video, audio streaming, and mixed traffic flow, the proactive wake-up scheduler reduces the power consumption of the baseline wake-up scheme without scheduler by up to 36%, 28% and 9%, respectively.

Recently, the concept of wake-up radio based access has been considered as an effective power saving mechanism for 5G mobile devices. In this article, the average power consumption of a wake-up radio enabled mobile device is analyzed and modeled by using a semi-Markov process. Building on this, a delay-constrained optimization problem is then formulated, to maximize the device energy-efficiency under given latency requirements, allowing the optimal parameters of the wake-up scheme to be obtained in closed form. The provided numerical results show that, for a given delay requirement, the proposed solution is able to reduce the power consumption by up to 40% compared with an optimized discontinuous reception (DRX) based reference scheme.

Recently, discontinuous reception mechanisms (DRX) and wake-up schemes (WuS) have been proposed to enhance the energy efficiency of 5G mobile devices and prolong the battery lifetime. The existing DRX and WuS use commonly pre-configured parameters that cannot be adjusted dynamically. In this paper, a novel wake-up scheduling (WuSched) concept is introduced to further improve the energy efficiency of WuS-enabled mobile devices while controlling the buffering delay in a dynamic manner. The main idea of WuSched is to use a fixed configuration of the wake-up scheme and adjust the scheduling of the wake-up signals dynamically based on actual traffic arrivals. For this purpose, two different optimization approaches of the wake-up scheduling concept are proposed, analyzed, and compared, namely offline and online wake-up schedulers (WuSched-Offline and WuSched-Online). First, the WuSched-Offline is analyzed analytically for Poisson traffic arrivals and optimized (offline) to balance the average delay and power consumption. Second, the WuSched-Online is proposed to take online decisions based on traffic prediction, which is able to deal with general and more complex traffic models. Towards this end, we develop a framework for the prediction of packet arrivals based on recurrent neural networks. Numerical results show that both wake-up schedulers outperform the ordinary WuS-based system where wake-up scheduler is not deployed. In particular, for predefined delay requirements of video streaming, audio streaming, and mixed traffic flow, the WuSched-Online reduces the power consumption of the baseline WuS by up to 36%, 28% and 9%, respectively. Results also show that the WuSched-Offline has slightly better energy efficiency than the WuSched-Online in the case of Poisson packet arrivals, as it is optimized for that, while its power consumption is slightly higher than that of the WuSched-Online scheduler for realistic traffic scenarios.

The limitations of state-of-the-art cellular modems prevent achieving low-power and low-latency Machine Type Communications (MTC) based on current power saving mechanisms alone. Recently, the concept of wake-up scheme has been proposed to enhance battery lifetime of 5G devices, while reducing the buffering delay. The existing wake-up algorithms use static operational parameters that are determined by the radio access network at the start of the user's session. In this paper, the average power consumption of the wake-up enabled MTC TIE is modeled by using a semi-Markov process and then optimized through a delay-constrained optimization problem, by which the optimal wake-up cycle is obtained in closed form. Numerical results show that the proposed solution reduces the power consumption of an optimized Discontinuous Reception (DRX) scheme by up to 40% for a given delay requirement.

Low-power and low-latency communication features are vital to extend 5G mobile devices functionalities beyond those of the current networks, and to introduce innovative services and applications. On the other hand, limitations of state-of-the-art cellular modules prevent designing and facilitating such features based on current power saving mechanisms alone. In this paper, a new wake-up signaling for 5G control plane is introduced, aiming to reduce energy consumption of cellular module in downlink. Performance of the proposed scheme in terms of false alarm and misdetection rates are investigated and evaluated. The obtained numerical results show that such a signaling can reduce power consumption of discontinuous reception (DRX) by up to 30%, at the cost of negligible increase in signaling overhead.

Mobile device batteries have severely limited capacities, due to constraints on size and weight of mobile devices. Therefore, energy efficiency of mobile devices plays an important role in their usability. Different power measurement studies show that cellular subsystem of mobile device is one of the major contributors to its energy consumption. Thus, reducing energy consumption of cellular subsystem is paramount. In this paper, a new concept of pre-grant message for control plane is introduced, aiming to reduce energy consumption of cellular subsystem in downlink, while discontinuous reception is activated. Performance of the proposed scheme in terms of false alarm and misdetection are investigated, and evaluated in AWGN and Rayleigh fading channel. The obtained numerical results show that such a signaling can reduce power consumption of mobile device by up to 70% for bursty data applications, at the cost of negligible increments in signaling overhead.

Due to non-negligible amount of energy consumption of state-of-the-art small cells at idle mode, energy efficiency of the overall network may decrease with densification. Therefore, energy efficiency in ultra-dense networks (UDNs) is one of the key challenges for mobile network operators (MNOs) to reduce their operative expenditure (OPEX), and to mitigate the carbon footprint. Low-power and low-cost dense networks are vital to extend next generation cellular network functionalities by improving network capacity in hotspot areas, and to deploy networks in short time periods. In energy harvesting networks, access points (APs) may perform both backhaul and access link data communication, simultaneously, removing UDN dependency on optical distribution network and electrical grid. In this paper, different power modes and essential signaling for operation of such APs are introduced, aiming to reduce energy consumption of UDNs by integrating energy harvesters into APs, equipped with wireless backhaul.

Carrier Aggregation (CA) is a promising approach to facilitate efficient use of fragmented spectrum in the next generation mobile communication networks. However, with CA the complexity of Resource Allocation (RA) increases in multi-carrier cellular networks. In this paper, an optimum RA algorithm is proposed to allocate Component Carriers (CCs), Resource Blocks (RBs), and Modulation and Coding Scheme (MCS) values among users. Our proposed method maximizes the total throughput, while at the same time maintains good throughput fairness among users. The numerical results show that the proposed method outperforms State-Of-The-Art (SOTA) solutions in both user-and cell-level performance metrics related to throughput, fairness and CC spectral efficiency.

Energy-constrained wireless networks and devices are mainly powered by batteries, which have severely limited capacities, demanding to be regularly recharged or replaced. Thus energy conservation plays a pivotal role in the operational lifetime of such networks. In this paper, the concept of a wireless powered wake-up receiver is studied, aiming to reduce energy consumption of the wireless node. The proposed wireless powered wake-up receiver scheme can be utilized for a range of energy-constrained wireless applications such as wireless sensor actuator networks, machine-to-machine communications, and the Internet-of-Things. Preliminary numerical results show that such a scheme can reduce energy consumption of wireless nodes considerably, at the cost of an extra low-power low-cost wake-up receiver.

Resource Allocation (RA) is one of the crucial elements in Long Term Evolution (LTE) networks, which has a tremendous impact on the network performance. However, complexity of the RA problem increases when both Carrier Aggregation (CA) and Multiple-Input Multiple-Output (MIMO) are enabled in the network. CA is a key functionality for LTE- Advanced (LTE-A) that enables Mobile Networ Operators (MNOs) to create large virtual carrier bandwidths for data hungry applications by aggregating available Component Carriers (CCs). In this paper, Resource Block (RB), Secondary CC (SCC), MIMO Transmission Mode (TM), and Modulation and Coding Scheme (MCS) selection is formulated jointly as an Integer Linear Programming (ILP). We prove that intractable integrality of the optimisation problem can be removed and relaxed to the Linear Programming (LP). Solving the LP obtains an optimal solution for the original ILP.

Carrier Aggregation (CA) is a key functionality for next generation wireless communication systems that enables operators to create larger virtual carrier bandwidths for data hungry applications by aggregating available Component Carriers (CCs). In this paper, the Resource Allocation (RA) optimisation problem in Orthogonal Frequency Division Multiplexing (OFDM) based wireless systems is studied with CA. We show that RA with CA can be formulated as a complex mixed integer programming optimisation problem under the practical constraints of transmit power and limited number of CCs available for each user. A two-step solution is proposed, Step 1: CC allocation is performed to satisfy users CA constraints and remove the intractable integer constraints of the optimisation problem, Step 2: power and SubCarrier (SC) allocation algorithm assigns resources among users sub-optimally. We propose two efficient methods based on our two-step solution with reasonably low complexity refer as Two-Step RA Algorithm (TSRAA) and Efficient RA Algorithm (ERAA). The performance of TSRAA and ERAA are compared with the highly complex Combinatorial Algorithm (COA) introduced as an optimal solution. Simulation results verify that TSRAA reaches to optimum solution and exploits the multi-CC diversity of wireless systems. Furthermore, numerical results show that ERAA achieves satisfying performance with very low complexity.