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Reallocating users/links to improve propagation.
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Dynamic load and spectrum usage management techniques can significantly improve the energy efficiency of mobile communications systems. This paper considers: (i) the opportunistic reallocation of traffic loads between bands to allow radio network equipment in the bands that the traffic is originated from to be powered down, and (ii) the opportunist...
Context in source publication
Context 1
... second concept, illustrated in Figure 2, is the opportunistic reallocation of links or users to more appropriate propagation bands at times when that spectrum becomes available. This decreases necessary transmission power due to improved propagation, or alternatively in a frequency reuse scenario, reallocation based on the necessary deployed cell density/radius and the given local propagation environment can be used to reduce inter-cell interference through minimizing power "leaking" into co-channel cells. ...
Similar publications
Automatic Repeat Request protocols (ARQ) are widely implemented in current mobile wireless standards such as HSDPA and LTE. In general, ARQ protocols are combined with channel coding to overcome errors caused by the lack of channel knowledge at the transmitter side. These protocols are called Hybrid ARQ protocols (HARQ). HARQ protocols ensure a goo...
Citations
... In wireless communication systems, power consumption usually reaches high levels, mainly in the BSs. Therefore, reducing transmission power and/or enabling sleep modes in the BS allow lowering operation power consumptions, as it is presented in [6]. ...
... The chosen FTP and HTTP ON/OFF model parameterizations are widely used in literature, taken from [2]. In this second approach, a separate simulation is performed for each hour in the 24 hour period for a given number of users being present (obtained in Fig. 3 from [6], scaled by the BusyLoad), where, at each second in the simulation duration, the simulation tallies the number of users present in each band according to the ON/OFF model being applied to each user. It then performs the power saving solution according to this number of users being present, and ascertains the power required in the before and after power saving solution cases. ...
... Finally, results are averaged over all simulations performed at each hour in the 24 hour period. Configuration parameters applicable to the simulation are given in Table 1 from [6]. ...
This paper determines the cost/revenue performance of a mobile communication system in an IMT-Advanced scenario with integrated Common Radio Resource Management (iCRRM). The iCRRM performs classic CRRM functionalities jointly with Spectrum Aggregation (SA), being able to switch users between non-contiguous frequency bands. The SA scheduling is obtained with an optimized General Multi-Band Scheduling (GMBS) algorithm with the aim of cell throughput maximization. In particular, we investigate the dependence of the throughput on the cell coverage distance for the allocation of users over the 2 and 5 GHz bands for a single operator scenario under a constant average Signal to Interference-plus-Noise Ratio (SINR), for the same type of Radio Access Technology and both frequency bands. The operator has the availability of a non-shared 2 GHz band and has access to part (or all) of a shared frequency band at 5 GHz. An almost constant gain near 30 % was obtained with the proposed optimal solution compared to a system where users are first allocated in one of the two bands and later not able to handover between the bands. It is shown that the profit in percentage terms decreases as the cell radius increases. These results allow for evaluating the impact of the revenue from the channel in the total revenue and in the profit, defined as the difference between revenues and costs, in percentage. Maximum profits of about 1270, 585 and 240 % have been obtained for prices of 0.10, 0.05 and 0.025 €/MByte, respectively, when iCRRM is employed, while profits of 990, 440, and 170 % have been reached with no iCRRM, i.e., simple CRRM. Finally, an energy efficiency strategy is proposed and analyzed, showing that there is significant transmission power saving potential through the opportunistic reallocation scheme.
... Naturally, any savings on this scale would have huge benefits for the company in terms of reduced energy bills, not to mention the implicit environmental benefits. An example provided below in Figure 5.4 shows results of simulations [19] that offer a power-saving benefit, expressed in terms of "energy reduction gain," if RBS transceivers for unused frequency bands are dynamically powered off. ...
... These concepts were introduced in authors' previous work in [6], [14] where we consider (i) the opportunistic reallocation of loads between bands to allow radio network equipment in the bands that the traffic originated from to be powered down, and (ii) the opportunistic selection of more appropriate spectrum band based on propagation characteristics to minimize necessary transmission power through improving propagation. In [7] we developed ON/OFF traffic models for different services like FTP, HTTP, video streaming etc. and investigated the proposed concepts under these models to evaluate the energy saving potential. In [8] we evaluated the concept of dynamically powering down the radio network equipment by opportunistically shifting users from cellular to Wi-Fi networks. ...
This paper investigates the green or energy efficient operation of cellular access networks through dynamic spectrum and traffic load management techniques. Different energy saving techniques are discussed along with applications in realistic multi-cellular scenarios. The use of base station cooperation is discussed. The outage probability analysis is also discussed for different energy saving techniques in order to satisfy a particular Quality-of-Service (QoS) threshold for different services. The analysis is supported by different base station power consumption models, traffic models, and realistic statistics of different base stations in London, UK. Results show a considerable power saving potential of up to 65% or more in base station power.
... The work carried out in this paper is also different from what presented in [13]. Simulations in the cited paper assume that operations related to energy saving automatically take place every time a user terminal joins or leaves a cell. ...
... Web traffic has been modeled as a continuous repetition of two states: a downloading period to retrieve a page from the web, and a waiting period, to parse and read the page [26,13]. The download time depends on the size of the web page and eventual embedded objects. ...
... The model for FTP sessions is similar to that for web sessions, except for the fact that there is no parsing time [27,13]. The download time exclusively depends on the size of the object to be transferred, which follows a Pareto distribution. ...
Cellular networks are rapidly evolving towards the fourth generation, thus providing a global infrastructure for wideband mobile network access. Currently, most of the energy consumption of such technology is by cellular base stations, which are not energy efficient—at least in terms of the transmission energy to “from-the-socket” energy consumption ratio. This paper addresses the problem of energy efficiency in cellular networks by taking advantage of the principles of cognitive networking, which promotes the creation of intelligent networks capable of self-configuration with minimal human intervention. In particular, this paper uses the concept of fuzzy cognitive maps to decide upon opportunistic traffic and user reallocations between radio network equipment operating in different spectrum bands to enable power saving modes by some subsets of the radio network equipment, and to utilize spectrum of more appropriate propagation characteristics to save transmission energy. The feasibility and performance of the proposed approach is investigated through simulations. Significant energy savings of some 25–30% are shown over a 72-h period, and blocking rate under the concept is shown to remain reasonable albeit exhibiting a high variance.
The chapter provides an accessible analytical framework that can be used to compare the energy consumption and throughput characteristics of different RAN configurations based on the Long Term Evolution (LTE) family of standards. The technical approach is useful for exploring how an LTE RAN may be upgraded in an energy efficient manner to meet the expected growth in mobile data traffic. The approach also allows particular energy saving techniques to be evaluated, such as deployment techniques (e.g., cell size and RAN topology) and power state techniques (e.g., sleepmodes). The analysis uses accurate energy consumption models of base station and access point equipment which account for the load independent as well as load dependent energy consumption effects. The Energy Consumption Gain (ERG) and Throughput Gain (TPG) figures of merit are used together with a new figure of merit called the Energy Throughput Gain (ETG) which reliably accounts for the difference in energy consumption and throughput between two distinct RAN configurations. The energy consumption and throughput performance of a greenfield RAN deployment scenario that uses different cell sizes and base station types is evaluated. The chapter then explores energy savings obtained from sleepmodes and HetNet deployments.
This paper investigates the energy savings a cellular operator can achieve in the access network by dynamically offloading users or traffic loads to Wi-Fi networks. The method used to analyze energy savings is presented, followed by detailed simulations using different traffic types. Results show that significant savings of up to 65-70% can be achieved by opportunistically powering down cellular radio network equipment as facilitated by the offloading of users to Wi-Fi.
