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With the introduction of Long Term Evolution (LTE) cellular networks, the spectral efficiency should be maximized according to the required high data rate. However, any increase in spectral efficiency will lead to an undesirable increase in power consumption, and thus lower energy efficiency will be obtained. Therefore, a new problem in radio resou...
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... Bandwidth [RB] Transmission Bandwidth Configuration [RB] Channel Bandwidth [MHz] Table 1 shows that the transmission bandwidth is smaller than the channel bandwidth due to the unused subcarriers. Figure 2 also shows the difference between the transmission bandwidth and the channel bandwidth due to the active resource block. ...
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High energy efficiency is critical for enabling massive machine-type communications (MTC) over cellular networks. This work is devoted to energy consumption modeling, battery lifetime analysis, lifetime-aware scheduling and transmit power control for massive MTC over cellular networks. We consider a realistic energy consumption model for MTC and mo...
Introduction The past decade has witnessed many significant advances in the physical layer of wireless communication systems in both theory and implementation. Traditionally, the design of existing cellular networks has focused on increasing the spectral efficiency, throughput, and transmission reliability, while minimizing the latency. The recent...
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... They concern the technological, architectural and network management aspects. Indeed, among the aspects that are the subject of works minimizing the energy consumption of access networks, we can mention: planning and sizing, user association and scheduling [5]. ...
The recent cellular wireless networks must not only ensure the communication between users known as human to human (H2H) but also between a huge number of machines for machine-type communication (MTC) or machine to machine (M2M). M2M can be considered as devices that can establish communications with other devices without any human intervention. M2M is also seen as the base of the vision of connected objects. It tempts a lot of attention because it can be seen as a new opportunity for network operators and Internet of Things (IoT) service. Today, there are several types of MTC-based applications spanning multiple domains, such as health, transport, smart meters and surveillance. The deployment of this kind of application in mobile cellular networks, particularly Long-Term Evolution (LTE) and LTE-Advanced (LTE-A), cannot be effective without controlling the challenges posed by the deployment of a large number of MTC devices in the same cell. Indeed, the deployment of a myriad of MTC devices will cause the challenge of resource allocation for assuring the quality of service (QoS). As MTC devices are equipped with a non-rechargeable battery, power consumption is also among the main challenges facing M2M communications over Long-Term Evolution networks. In this article, we focused on the radio resource management in downlink LTE networks for M2M communication by a study of scheduling techniques that are: proportional fair (PF), exponential proportional fair (EXP)/PF), maximum-largest weighted delay first (MLWDF) and frame-level scheduler (FLS). We considered the video and VoIP services as real-time (RT) streams as well as best effort (BE) as non-real-time (NRT) streams, considering the QoS criteria in terms of throughput, fairness and energy, in order to conclude a distinct vision on the quality of experience provided by these algorithms. The results of analysis indicate that MLWDF scheduler is the best according to the energy and spectral efficiency than PF, EXP-PF and FLS techniques, while FLS is better in terms of quality of service (QoS) metrics for RT services.
Power and spectrum efficiency have been the concerns for the customers in Long term evolution (LTE) uplink system. On one hand, due to the limited spectrum, it is difficult to provide a high quality of service (QoS) to the user equipment (UE) in a heavy traffic load. On the other hand, people have been paying more attention to the energy efficiency because of the battery constraint and the decreasing size of the mobile devices. Even though the issues mentioned above have been addressed in the literature, the study about tradeoff design of both two issues is sparse. The rationale for the tradeoff is that due to the fast changeable channel conditions and unpredictable data requests from UEs, adopting the unique resource allocation scheme, either power-saving (PS) or spectrum-saving (SS) scheme, is not flexible. Therefore, this paper proposes a tradeoff method to dynamically choose either PS or SS scheme according to the changeable UE's request and channel conditions. In the proposed system, multi-class UEs are considered. The performance of the PS-only scheme, SS-only scheme and the proposed hybrid scheme (H-PSSS) are analyzed and compared. Results show that the proposed hybrid scheme achieves the desired performance.
Energy efficiency in wireless broadband network is increasingly crucial because of the shrinking size and the battery constraint of mobile devices. Therefore, to save the power of user equipment (UE) is an important issue in practical network applications. Meanwhile, under the condition of limited spectrum and heavy traffic load in system, spectrum efficiency is also important resulting from the pursuits of high quality of service (QoS) and high data rate. In this paper, we propose and compare two extreme radio resource allocation schemes: the power-saving (PS) oriented scheme and the spectrum-saving (SS) oriented scheme in LTE uplink system. The PS oriented scheme minimizes the power consumption in allocating radio resource. On the contrary, the SS oriented scheme considers the efficient radio resource utilization to maximize the system throughput. Although the scheduling purposes are different, both schemes consider the changeable channel condition, QoS satisfaction, and continuous resource blocks (RB) for uplink scheduling in LTE network. Simulation results of system throughput, power consumption, and transmission quality (e.g. packet dropping rate) are compared and analyzed. As these two schemes are designed in minimizing the power consumption and maximizing the spectrum utilization, respectively, the experimental results can be applied as the referential bounds for the study of adaptive scheduling schemes.
Energy saving plays a significant role in the communication system. Moreover the traffics of 3GPP are expanding and getting ever more complex. We can save more energy by taking advantage of the fact that different traffics have different QoS requirements. This paper proposes a model for such kind of optimization problems. However, it is difficult to find the optimal solution. So in the view of engineering, we propose a scheme, Two Levels Water-Filling Scheme (TLWFS), to improve the energy efficiency while guaranteeing the QoS requirements. In TLWFS, firstly, we classify the traffics into two categories, which are Rate Constrained Traffic (RCT) and Rate Non-Constrained traffic (RNCT). Secondly, at the first water-filling level, the high SNR Resource Blocks (RBs) are selected to guarantee the RCT, with traditional water-filling algorithm. Finally, at the second water-filling level, the energy and RBs left are used to transfer the RNCT, with directional water-filling algorithm. Numerical results indicate that the TLWFS works well in LTE system, with the energy consumption decreased by 10% with TLWFS, compared to traditional power allocation scheme.
The LTE standards is leading standard in the wireless broadband market. In order to accommodate the increased demand for mobile data services the radio interface in the LTE standard is enhanced with advanced technologies such as OFDMA (Orthogonal Frequency Division Multiple Access) and MIMO (multiple antenna) techniques. The Radio Resource Management at the base station plays major role in satisfying the users demand for high data rates and QoS. Resources for both downlink and uplink transmission need to be assigned such that the capacity, throughput, and cell edge performance are optimized. This paper evaluates a cross layer scheduling algorithm that aims at minimizing the resource utilization. The algorithm makes decisions regarding the channel conditions and the size of transmission buffers and different QoS demands. The simulation results show that the new algorithm improves the resource utilization as well as provides better guaranties for QoS.
