Available online at www.sciencedirect.com

H O S T E D B Y

Digital Communications and Networks (2015) 1, 152–159

http://dx.doi.org/12352-8648/& 2015 Carticle under the CC

☆This work was suResearch and Deve2014AA01A705) andChina (No. 61201231

nCorresponding auE-mail addresses

wangyuanyuan@ict.azhouyiqing@ict.ac.csjl@ict.ac.cn (J. Shi

journal homepage: www.elsevier.com/locate/dcan

A super base station based centralizednetwork architecture for 5G mobilecommunication systems$

Manli Qiana,b, Yuanyuan Wanga,b, Yiqing Zhoua,b,n, Lin Tiana,b,Jinglin Shia,b

aInstitute of Computing Technology, Chinese Academy of Sciences, ChinabBeijing Key Laboratory of Mobile Computing and Pervasive Devices, Beijing 100190, China

Received 31 December 2014; received in revised form 12 February 2015; accepted 28 February 2015Available online 19 March 2015

0.1016/j.dcan.201hongqing UniversiBY-NC-ND license

pported in part bylopment Programthe National Na).thor.: qianmanli@ict.acc.cn (Y. Wang),n (Y. Zhou), tianlin).

AbstractTo meet the ever increasing mobile data traffic demand, the mobile operators are deploying aheterogeneous network with multiple access technologies and more and more base stations toincrease the network coverage and capacity. However, the base stations are isolated from eachother, so different types of radio resources and hardware resources cannot be shared and allocatedwithin the overall network in a cooperative way. The mobile operators are thus facing increasingnetwork operational expenses and a high system power consumption. In this paper, a centralizedradio access network architecture, referred to as the super base station (super BS), is proposed, asa possible solution for an energy-efficient fifth-generation (5G) mobile system. The super basestation decouples the logical functions and physical entities of traditional base stations, so differenttypes of system resources can be horizontally shared and statistically multiplexed among all thevirtual base stations throughout the entire system. The system framework and main functionalitiesof the super BS are described. Some key technologies for system implementation, i.e., the resourcepooling, real-time virtualization, adaptive hardware resource allocation are also highlighted.& 2015 Chongqing University of Posts and Telecommunications. Production and Hosting by Elsevier B.V.

This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

5.02.003ty of Posts and Telecommunicatio(http://creativecommons.org/lic

the National High Technologyof China (863 Program No.tural Science Foundation of

.cn (M. Qian),

dd@ict.ac.cn (L. Tian),

1. Introduction

With the rapid development of smart phones and mobileinternet applications, mobile users require ever increasingwireless transmission data rates. According to the CISCOVisual Network Index (VNI) report, the global mobile datatraffic will increase 13-fold between 2012 and 2017, growingat a compound annual growth rate of 66%, and reaching 11.2

ns. Production and Hosting by Elsevier B.V. This is an open accessenses/by-nc-nd/4.0/).

153A super base station based centralized network architecture for 5G mobile communication systems

exabytes per month by 2017 [1]. To meet the explosivemobile data traffic demand, various measures have beentaken to enhance the system capacity, such as morespectrum, smaller cells, employing advanced wireless tech-nologies such as orthogonal frequency division multiplexing(OFDM) [2] and multiple-input multiple-output (MIMO).Nevertheless, the peak data rate from 2G to 4G systemhas only increased at a compound annual growth rate of 55%[1]. There is a big gap between the traffic demand andnetwork capacity and the gap is further growing.

In future 5G mobile communication systems, a number ofpromising techniques have been proposed to support a threeorders of magnitude higher network load compared to whatoperators are experiencing today. One possible approach isto increase the density of wireless access points [3].However, if the conventional mobile network architecturebased on distributed base stations (BSs) is employed, moreand more BSs will be needed, which brings mobile operatorsbig challenges such as

�

a rapidly increasing network operational expense causedby the construction, maintaining and power consumptionof a large number of BSs;

�

severe inter-cell interference, due to the dense deploy-ment of BSs, which are logically independent of eachother without full cooperation;

�

low system hardware resource utilization rate. Note thatunder current network architecture, each BS must bedesigned with high capacity to support the maximumpossible traffic load in its cell. When the traffic load islow, most of the capacity is wasted, because the hard-ware resource of BSs, such as computation and memorycapacity, cannot be shared among different BSs sincethey are isolated from each other.

Tab. 1 Key techniques and performance comparisonbetween C-RAN and super BS.

Items C-RAN Super BS

BBUcomponent

GPP platform withhardware accelerator

ReconfigurableDSP

Virtualizationtechnique

Traditional IT-basedvirtualization

A process-levelvirtualization

Performanceper Watt

Low High

Real-timeperformance

Low High

Openness ofthe interface

High Low

Obviously, a dense cellular network based on conventionalindependent BSs is not suitable for 5G systems. Therefore, acentralized cellular network architecture has been proposedand it has become a hot research topic in both academia andindustry. China Mobile announced a centralized radio accessnetwork architecture (C-RAN) in 2009 [4], which incorporatescentralized baseband pool processing, cooperative radio withdistributed antennas equipped with remote radio heads (RRHs),and real-time cloud infrastructures. Following C-RAN, wirelessnetwork cloud (WNC) [5] by IBM and LightRadio [6] by Alcatel-Lucent and Bells Labs are also proposed as possible solutions forthe future centralized wireless networks. Moreover, a RANevolution project P-CRAN is set up by NGMN in 2011 [7] tostudy the requirement, solution and standardization of C-RANfor a future radio access network architecture providingoptimized operations, higher efficiency and enhanced perfor-mance. The main idea of these new architectures is to decouplethe radio frequency (RF) and baseband processing functions,which have been co-located in traditional BSs. Only an RRH islocated in each cell site. The building baseband units, referredto as BBUs, which perform the baseband processing functions intraditional BSs are now aggregated and moved into a centra-lized location, referred to as the BBU pool. The RRHs areconnected to the BBU pool through high bandwidth opticalnetworks. With this centralized network architecture, the

network operating cost and power consumption can be reducedsignificantly due to the relatively simple locating of RRHs andlow cost maintenance of BBUs. The C-RAN network trial tests byChina Mobile has shown that the system OPEX, CAPEX andpower consumption with C-RAN decreased by 50%, 15%, and71%, respectively, compared to the respective values in atraditional mobile system.

Although centralized network architectures are promisingfor 5G systems, there are various challenges if a largenumber of cells need to be centralized. One big challenge isto construct a super-high capacity BBU pool, which handlesthe baseband processings for a large number of cells. InC-RAN, the BBU pool is deployed on standard GPP platform,such as the standard IT server with x86 architecture, and anadditional dedicated hardware accelerator is also added oneach server for the computation-intensive physical layerprocessings [8]. Traditional IT-based virtual machines (VMs)are installed on the servers, where different kinds of BSscan be easily set up through a unified open interface.However, it is reported that only 3–6 LTE subcarriers canbe processed by a standard server with a size of 2 rack units,with a relatively high power consumption, i.e., 80 Watts peran LTE subcarrier, on the GPP based C-RAN BBU pool.Although the computational capability of the GPP platformwill definitely increase and the average power consumptionwill decrease year by year, driven by the Moores Law, thereare also concerns that GPPs and the traditional IT virtuali-zations, which are originally designed and optimized fornon-real time tasks, may not be able to satisfy the real-timeprocessing requirement of 5G systems [8].

In this paper, we present a logically distributed but physicallycentralized mobile network architecture, referred to as thesuper base station (super BS), for the 5G system. The BBU poolis constructed with digital signal processors (DSPs) arrays. Theprogrammable DSPs have been widely employed in currentcommunication systems with advantages such as low powerconsumption and high capability to handle real-time processing.It is expected that in the DSP based super BS system, anaverage power of 5–10 Watts per an LTE subcarrier can beachieved in the BBU pool. However, compared to GPP basedBBU pool, a big challenge for super BS is how to manage all thehardware resources, such as computing resources and mem-ories, in a flexible, highly efficient and real-time way. Aprocessing-level real-time virtualization technique is proposedin this paper for the hardware resource management in the

M. Qian et al.154

super BS. Transparent abstractions of system resources are firstprovided. Then one or more virtual BSs (VBSs) with differentstandards are built up. The system resources are directlyallocated to these VBSs in a cooperative and efficient way bythe centralized resource management center, without anyinterruption of operating systems, so that real-time commu-nication processing can be guaranteed. The main differencesand the performance comparison between the C-RAN and superBS are described in Tab. 1.

In the following sections, we will first give a comprehen-sive description of the super BS system architecture,followed by the discussion of the key technologies in systemimplementation.

2. Super BS based centralized networkarchitecture for 5G mobile systems

The centralized network architecture based on super BS isshown in Fig. 1. Similar to C-RAN, it consists of three mainparts: the distributed RRHs located at cell sites, the highcapacity and low latency optical network and the super BS.Moreover, the super BS is further divided into three parts:the high-performance multi-mode reconfigurable BBU poolbased on DSPs, the multi-mode higher layer protocolprocessing unit (PPU) pool based on GPPs, and the globalcentralized resource management center (GRMC).

The distributed remote radio heads (RRHs) are antennaarrays that consist of multi-band radio frequency (RF)processing units, which are deployed exactly in the sameway as the antennas in traditional BSs. All the RRHs areconnected to the BBU pool via a high bandwidth and low-latency optical network, and a radio frequency switch(RFS). Under the control of the GRMC, the mapping betweenRRHs and BBUs can be dynamically adjusted by simplychanging the switch policy. For example, the uplink base-band I/Q data from an RRH are firstly transmitted to theBBU pool as an input to the RFS. Then the GRMC selects theoutput in the RFS, where the uplink data are sent to acorresponding BBU for further processing, considering thecurrent working load of all the BBUs in the BBU pool.

Fig. 1 Super BS system architecture.

Moreover, according to the cell load, the GRMC can adjustthe configurations of RRHs, and turn on or switch off theRRHs to guarantee the network coverage in an energyefficient way.

The super BS is the key of the new centralized architec-ture for 5G mobile systems, where the logical functions andphysical entities in traditional BSs are decoupled. Differenttypes of hardware resources, i.e., the antennas, BBUs, PPUsand BS management units, are horizontally shared. By usingthe resource pooling and real-time virtualization technolo-gies (described in Section 3), the super BS provides atransparent abstraction for these hardware resources andtransforms them into one or more logical entities. Thus, oneor more VBSs with different standards can be easily built upwith these entities through a unified and open interface.

In the super BS, the high-performance multi-modereconfigurable BBU pool consists of large scale program-mable DSP arrays, which perform the physical layer proces-sing procedures. With resource pooling and virtualizationtechnologies, the BBUs are shared among all the VBSs andcan be dynamically allocated to different VBSs, based onthe requirements of VBSs, where the system hardwareresource can be fully utilized.

The multi-mode higher layer PPU pool refers to aresource pool for the higher layer protocol processing, suchas Layer 2 and Layer 3 over the air interface. The PPU poolconsists of large scale GPP platforms, such as PowerPC, ARMprocessors and x86 servers, so the higher layer protocolfunctionalities are implemented as software programs run-ning on GPPs. The programs for different protocols can bedynamically configured on each PPU by the GRMC, basedon system configuration policies. The inter-connectionsbetween logical protocol processing units and the basebandprocessing units follow standard wireless interfaces, such asIub and Abis. High-speed 10-GbE is used to exchange themassive protocol data between the PPU and BBU pools.

The global centralized resource management center(GRMC) is the control center of the super BS system. Itdetermines the allocation of radio resources (i.e., time,spectrum, power, space) and hardware resources (i.e.,BBUs, PPUs) to each VBS. For example, since the real-timechannel status information of each cell, such as the loadinformation and channel quality, are all transferred to thesuper BS, the advanced physical layer transmission techni-ques and resource management schemes such as CoMP andeICIC can be applied in a centralized and cooperative way,where the inter-cell interference can be greatly decreased.Moreover, under the control of GRMC, the hardwareresources can be dynamically allocated to different VBSsaccording to their traffic load profiles, where the hardwareresource utilization is maximized. Through the joint radioresource and hardware resource allocation, different typesof system resources can be managed in a cooperative way,where a future green, energy-efficient wireless network canbe realized.

3. Key technologies

As a large amount of hardware devices are physicallycentralized in the super BS, one of the key challenges isto effectively construct the resource pool, such as the BBU

155A super base station based centralized network architecture for 5G mobile communication systems

pool and PPU pool, where a high-bandwidth and low-latencyinterconnection between different hardware resources isprovided. Moreover, how to dynamically build up differenttypes of VBSs for the cells and allocate the hardwareresources in the centralized resource pools to the VBSsbased on their demands are the other two importantchallenges in the system design.

3.1. Large scale resource pooling

In the super BS system, there is no fixed mapping betweenthe hardware resources and VBSs. A large amount of BBUsand PPUs are physically grouped together and form the BBUand PPU pools, which enable the statistical multiplexing andcooperative allocation for different resources. Note that incurrent mobile systems, there are BS products that separatethe RRH and BBU functions, where the physical layerprocedures from a group of BSs are processed in a smallsize BBU pool [4]. However, the mapping between the RRHand BBU is predefined and the hardware resources ofdifferent BBUs cannot be dynamically shared by differentBSs. So the super BS is fundamentally different from theseBS products and new technologies are needed to realize theresource pooling. Moreover, as a large amount of data (e.g.,more than 10 Gbits/s) needs to be exchanged betweendifferent BBUs and PPUs within a millisecond time period,the bandwidth and data exchange latency among the BBUsand PPUs are two most critical limitations when construct-ing the resource pool.

As shown in Fig. 2, a 4-layer interconnection framework isproposed to construct the BBU and PPU pools in the superBS. Based on the open micro-telecom computing architec-ture (mTCA) and advanced telecom computing architecture(ATCA), a given number of BBUs/PPUs are first connected toa BBU/PPU board through PCIe interface. Different BBU/PPU boards are then connected to each other through GbEhigh-speed backplane and form the BBU/PPU sub-pool.Finally, the BBU/PPU pool is constructed by several BBU/PPU sub-pools, where a large number of air interfaceprotocol data can be exchanged between different sub-pools through a 10 GbE optical fiber network. By using this4-layer inter-connection framework, a maximum of 20 Gbpsthroughput can be supported in a single BBU/PPU boardwith low latency. Moreover, by using this open framework,the network operators can easily expand system capacity bysimply constructing and inserting new resource pools in the

Fig. 2 Resource pooling framework in super BS.

system, without any interruption to current networkservices.

Large scale resource pool synchronization: In mobilecommunication systems, it is important to keep the syn-chronization among BSs. The BSs in traditional systems canachieve both frequency and time synchronization, andensure the long-term stability of their clock frequenciesby synchronizing their respective local clocks to GPS signals.However, the GPS-based synchronization method has severalproblems, such as the GPS antenna has specific require-ments on installation environment, a high failure rate and itcannot support remote maintenance. New technologieshave been proposed to construct a precisely synchronizednetwork, such as the IEEE 1588 Precision Time Protocol(PTP) [9], which provide clock synchronization in a high-speed local area network, and the one pulse per second(PPS) and time of day (ToD) time interface for precisiontime synchronization [10].

Although the synchronization among all BSs in traditionalnetworks is not easy to achieve, it becomes simple in thesuper BS system, since all the VBSs are co-located and onesingle timing source can be used for all hardware units. Inthis paper, we propose a two-layer synchronization mechan-ism for the super BS, where all the hardware units in thesystem receive the same clock signal input. In the first layer,a centralized clock distribute unit (CDU) is first synchro-nized to the GPS. Then the CDU generates a 1 PPS synchro-nous reference signal, i.e., the current system framenumber, ToD, and transfers the signal to all the hardwareunits in the resource pool. In the second layer, there is aclock agent on each hardware, i.e., the BBU or PPU. Oncereceiving the synchronous reference signal from the CDU,the clock agent will first calculate the circuit level transmis-sion delay from the CDU to its master hardware. Based onthe synchronous reference signal received and the transmis-sion delay compensation, all the hardware units in theresource pools are synchronized to the CDU.

3.2. Real-time virtualization

The large scale BBU and PPU pools with high-speed and low-latency interconnections enable the global resource sharingamong various VBSs in the super BS, which could be realizedby virtualization technologies. With virtualization, a trans-parent abstraction of the hardware resources is providedand transformed into one or more logical versions that canbe used by different VBSs, while the services provided tothe end users are exactly the same way as traditional BSs[11,12]. The problem is how to realize real-time virtualiza-tion. Note that in the C-RAN and WNC, the resourcevirtualization is realized through traditional IT-based tech-niques, such as Xen and Vmware [12]. In these systems, thesoftware and hardware resources are decoupled and sharedbased on the operating system. An operating systemabstraction layer is created to manage the processingrequests from different VBSs. However, the creating orswitching tasks from different VBSs will cause high systemoperational cost and extra processing latency [12], wherethe critical data processing latency requirement in wirelesscommunication is hard to be guaranteed [4].

M. Qian et al.156

The real-time virtualization problem can be tackled inthe DSP-based super BS system by a process-level virtualiza-tion scheme, where the operating system abstraction layeris omitted. Fig. 3 shows the four-layer real-time virtualiza-tion framework for the super BS: hardware resource layer,virtual resource layer, virtual Base Station layer and virtualnetwork application layer from bottom up. All these layersare controlled by the GRMC directly without the involve-ment of operating system abstraction layer.

In the hardware resource layer, different types of hard-ware devices are decoupled and there is a hardwareresource abstraction entity on top of each device, whichis used to manage the corresponding device. The processingcapabilities from different devices are then divided intosmaller pieces, such as multi-threads for different physicallayer procedures, and a unified operational interface isprovided by the hardware resource abstraction entity.Unlike the traditional IT-based virtualization, a process-level virtualization is implemented in the hardwareresource layer, where different kinds of hardware resourcescan be scheduled directly without the interruption ofoperating system. Thus the resource loss and system opera-tional delay during the scheduling of hardware resources areminimized.

In the virtual resource layer, the hardware resources areaggregated and form the virtual resource pools, i.e., theBBU pool, PPU pool. The resource mapping between thevirtual resource pool and hardware resources is maintainedin this layer. It also provides a unified operational interfaceto higher layers. In the VBS layer, the VBS managemententity will allocate antennas, BBUs and PPUs, provided bythe virtual resource layer to different types of VBSs,according to the service and operational requirement fromupper layers. The VBS layer provides a programmable andreconfigurable interface to the virtual network operators,such as the virtual GSM, 3G and LTE network operators, whocan be easily built up and provide different network servicesbased on the requirement of end users. Under this 4-layervirtualization framework, the network operators no longer

Fig. 3 The real-time virtualizatio

need to focus on the hardware resources, but only on how touse the virtual resources provided by the VBS layer. In thelower layers, the hardware resources can be used andshared by all VBSs, thus the resource utilization is greatlyimproved.

Seamless online resource migration: In order to improvethe system resource utilization, the processing require-ments from different VBSs are dynamically scheduled todifferent hardware resources in the super BS, through onlineresource migration. For example, when system traffic loadis low, the processing requirements from different VBSs canbe mapped to the same hardware resource; when some ofthe hardware resource is in a high utilization status, part ofthe processing requirements can be transferred to thehardware devices with a low utilization status. In this way,the hardware resources can be fully utilized. Moreover,when some of the hardware devices fail, the processingprocedures can be transferred to other devices immedi-ately, hence the system reliability is guaranteed.

In the super BS, a seamless online resource migrationscheme is proposed based on the radio network controller(RNC) relocation procedure in mobile communication net-works and the traditional virtual machine migration incomputer networks. The main idea is to logically separatethe processing task and data context during the resourcemigration process. The processing task is the physical layeror higher layer procedures, e.g., the turbo encoding/decoding process. The data context is the correspondingcomputing information during the procedures, i.e., thememory, data structure, and status machine information.As shown in Fig. 4, when GRMC initiates a resource migra-tion operation for the BBU or PPU processing task (a), theBBU or PPU processing task (a) using hardware resource 1 isfirstly suspended and the data context is transferred tohardware resource 2. Then a corresponding BBU or PPUprocessing task (a) is re-built on hardware resource 2. Thevirtual resource layer updates the resource mapping for thevirtual resource 1 and binds it to hardware resource 2. Theadded data context that is generated by hardware resource

n framework for the super BS.

Fig. 4 Seamless online resource migration in the super BS.

Fig. 5 Different hardware resource mapping schemes in the super BS.

157A super base station based centralized network architecture for 5G mobile communication systems

1 during the resource migration procedure is further trans-ferred to hardware resource 2 to ensure the seamless datatransfer and the correct order of the data information.After that, the BBU or PPU processing task (a) is terminatedand all the corresponding resources are withdrawn byhardware resource 1. Finally, the new BBU or PPU proces-sing task (a) is re-built and the resource migration proce-dure for the virtual resource 1 completes.

3.3. Adaptive hardware resource allocation ondemand

As the traffic load for different cells fluctuates greatly overtime [4], when a VBS is in a high traffic load, more hardwareresources are required. When the traffic load is low, theredundant hardware resources could be dynamically re-assigned to other VBSs with a higher traffic load. Throughadaptive hardware resource allocation, the network traffic

tide effect [4] can be effectively solved and the hardwareresource utilization can be maximized. Moreover, some ofthe hardware resources can be turned off when the systemis in a low traffic load to save power.

Load diversity based hardware resource allocation: Themain goal of the hardware resource allocation is to max-imize the hardware resource utilization by finding anoptimal mapping between the BBU/PPU pool and the VBSs,according to the dynamics of system traffic load. Theoreti-cally, the optimal resource allocation can be obtained bysequentially scheduling the hardware resources to eachVBS, until all VBSs processing requirements are satisfied.When the system traffic load distribution changes, thehardware resource mapping between the BBU/PPU pooland the VBSs is changed accordingly, so that the networktraffic tide-effect is adapted and the hardware resourceutilization is maximized. However, the system hardwaremapping for all the VBSs needs to be adjusted whenever thetraffic load distribution changes by using this optimal

M. Qian et al.158

solution. In system implementation, when the hardwareresource for a given VBS shifts from one BBU/PPU to anotherBBU/PPU, all processing tasks need to be suspended and thecommunication context need to be transferred. Thus a highsystem computational overhead will be caused by frequentresource allocation adjustment, especially in a large scalesystem.

To fully exploit traffic load diversity and avoid thefrequent global system resource adjustment, a semi-staticresource allocation scheme with load diversity (LDA) [13] isproposed. Note that, if the VBSs covering adjacent cells aremapped to the same BBU/PPU sub-pool, it is highly possiblethat the resource utilization for the corresponding BBU/PPUsub-pool will be simultaneously either high or low. This isbecause the network loads of adjacent cells usually have asimilar time-geometry pattern. Thus a large amount ofhardware resources are required to handle the peak hourtraffic load, while the hardware resource utilization will bequite low when the traffic load for those adjacent cells goesdown. Thus, the main idea of the LDA scheme is to map theVBSs covering distant cells to the same BBU/PPU sub-pool.As shown in Fig. 5, an appropriate set of VBSs with oppositetraffic load distribution is first mapped to the same BBU/PPU sub-pool. When the traffic loads for the VBSs change,the resource allocation for the VBSs that are mapped to thesame BBU/PPU sub-pool is adjusted with a higher priority.If the remaining hardware resources on that particular BBU/PPU sub-pool cannot satisfy the requirement of its servingVBSs, new BBU/PPU sub-pools are then assigned and theVBSs with a high traffic load are migrated to the new BBU/PPU sub-pool. Within a given BBU/PPU sub-pool, theresource mapping between the BBUs/PPUs and the VBSscan be converted to a bin-packing problem, which can besolved by heuristic algorithms, such as the simulatedannealing and first fit algorithms.

Fig. 6 compares the system power consumption in theBBU pool of the proposed LDA scheme with that of the staticresource allocation in conventional cellular networks andthe optimal solution described above, under a small sizesuper BS system with 50 cells during a workday. Half of thecells represent business areas while half of the cells

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

100

200

300

400

500

600

Time

Sys

tem

ene

rgy

cons

umpt

ion

(W)

LDAOptimalConventional

Fig. 6 System power consumption comparison under a smallsize super BS system with 50 cells during a workday.

represent residential areas, the traffic profile for each cellis collected in [4]. It can be seen that our proposed schemeconsiderably decreases the system power consumptioncompared to the static resource allocation scheme inconventional cellular networks. The power consumptionfor the proposed LDA scheme is slightly higher than theoptimal resource allocation scheme under the high systemtraffic load scenarios. However, as the LDA scheme maps theVBSs with opposite traffic load trends to the same BBU sub-pool, the hardware resource can be adjusted within the BBUsub-pool. Thus the system computing overhead caused bythe resource migration between different BBU sub-pools canbe decreased significantly.

4. Conclusion

There has been a consensus that the future 5G mobilesystem will be a heterogeneous network, where multiplewireless access technologies coexist and provide high-bandwidth services to end users. However, an increasednetwork operational cost, high power consumption and lowresource utilization will be caused by the dense deploymentof multi-mode wireless access points. The centralizedsystem architecture is a promising solution to the abovechallenges. In this paper, logically distributed but physicallycentralized new network architecture based on the super BSis proposed. Different types of system resources are hor-izontally shared among all VBSs through the resourcepooling techniques. To guarantee the real-time processingin communication networks, a 4-layer real-time virtualiza-tion framework is introduced. Finally, a hardware resourceallocation scheme with load diversity is presented, wherethe hardware resources can be dynamically allocated todifferent VBSs according to their traffic load profiles. Smallscale system testing results have shown that the powerconsumption in the BBU/PPU pool can be greatly decreasedand system hardware resource utilization can be increasedunder the super BS system architecture.

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