Carrier Aggregation - Opportunities and Challenges
Jedrzej Stanczak
Faculty of Electronics and Telecommunications Poznan University of Technology
Poznan, Poland
Email: jedrzej.r.stanczak@doctorate.put.poznan.pl
Mateusz Buczkowski
Faculty of Electronics and Telecommunications Poznan University of Technology
Poznan, Poland
Email: mateusz.buczkowski@put.poznan.pl
Abstract—Carrier Aggregation (CA) is one of the most sub-stantial functionalities introduced in 3GPP Release 10. In terms of spectrum usage it provides extra flexibility for the mobile network operators. Simultaneously it can offer increased peak throughput to the users. Nevertheless, undisputed benefits of Carrier Aggregation come at a price. This article is aimed at describing the basics of CA technique and the challenges which have to be tackled. The attention is particularly focused on Radio Resource Management associated with CA. Future trends and various operating environments for CA are outlined. The article partially encapsulates current achievements of SOLDER research project which, among the others, strives for a development of robust RRM mechanisms for CA in imminent mobile networks.
I. INTRODUCTION
Carrier Aggregation (CA) is a functionality of paramount importance. Its introduction in 3GPP Release 10 has been a significant part of an evolution towards LTE Advanced (LTE-A). The main goal of CA solution is to make 100 MHz (i.e. 5 times 20 MHz) of bandwidth accessible to the Downlink (DL) users. In Release 10 an 11, though, the aggregation of only 2 or 3 Component Carriers (CC) is feasible. A flexibility of combining CCs is a crucial mechanism for Mobile Network Operators (MNO). It is especially desired with respect to a rapidly growing demand for data transmission. Such tendency is undisputed and will gain momentum throughout the next few years. Those predictions are reflected in the reports issued by the most influential players from mobile network industry (e.g. [1] and [2]). The enlargement of offered spectrum is one of the methods to boost data rates and satisfy aforementioned end-user requirements. Carrier Aggregation is specified for Downlink and Uplink and can be deployed in FDD (Frequency Division Duplex) and TDD system (Time Division Duplex). In conjunction with MIMO technique (8 x 8 variant, 5 x CC) theoretically it can enable a DL user to obtain a mind-boggling throughput of 3 Gbps. However, such impressive achievement come at a price of increased complexity. CA for LTE-A requires new functionalities and enhancements, for example with respect to Radio Resource Management (RRM). Additional frequency assets need to be managed appropriately in order to take the full advantage of this solution. Further-more, CA is already considered not only for traditional LTE deployment (i.e. in Homogeneous network). Heterogeneous networks which comprise a blend of macro and small cells are becoming ubiquitous. Thus, mechanisms to efficiently incorpo-rate CA into such environments are highly desired. Eventually,
various Radio Access Technologies (RATs) start to coexist what inherently means the problem of Carrier Aggregation between separate RATs has to be addressed either. All aspects that have been pointed out above are encompassed in SOLDER research project (see [4]). This endeavour is aimed at providing means to effectively aggregate CCs in HetNets and h-RATs (heterogeneous RATs). It focuses on physical layer techniques as well as higher layer solutions including link adaptation, scheduling and radio resource management.
The rest of the article is organized as follows. We elaborate on ’traditional’ Carrier Aggregation technique. Afterwards a study on CA associated with HetNets and h-RATs is provided. Finally, the main points are recalled and future research tasks are outlined.
II. CAINHOMOGENEOUS ENVIRONMENT AND IN HETNETS
The most straightforward way of aggregating frequency resources is to combine two (or more) adjacent carriers which belong to the same band. This is one of the options specified for CA and denoted by ’intra-band, contiguous CA’ (see Fig. 1). This is the most convenient case - also from RF architecture’s point of view (i.e. there is no need to provide a separate RF front-end). On the other hand - it is a rare case Mobile Network Operator has wide contiguous spectrum within single band. More often frequency resources are fragmented within certain band or even dispersed over separate bands. The former case is labeled as ’intra-band non-contiguous CA’ whereas the latter is described as ’inter-band CA’. Both provide additional flexibility to MNOs as scattered spectrum can be jointly offered to a single user. However, the obvious drawback of such approach is much more complicated RF equipment, which should provide proper parameters in wider frequency range. Also propagation properties will be different for all CCs in inter-band case, which requires more advanced algorithms like Link Adaptation, Power Control, Handover etc. In traditional FDD systems each DL carrier has its counterpart in UL. This prerequisite does not have to be met in LTE-A where it is feasible to have asymmetric configuration. Usually the number of DL CCs is larger than the amount of UL CCs. Each LTE-A user has one Primary Cell (PCC) which is responsible for RRC signalling and general controlling tasks. In addition, from one to four Secondary Cells (SCC) can be configured for such user.
Fig. 1. Aggregation of five Component Carriers (CC)
It is quite intuitive that an efficient management of supple-mentary CCs is a complex challenge. Several factors need to be taken into account prior to resource assignment. The most straightforward metric which is used to select a Component Carrier is Reference Signal Received Power (RSRP) level estimated by the UE (User Equipment). However, such simple measure might be insufficient in composed networks incor-porating LTE-A (with Carrier Aggregation). Thus, additional criteria should be taken into account. A comprehensive CC assignment algorithm should consider instantaneous load on each CC. It can be done either by means of interference measurement on each CC or by ordinary user count. Generally speaking - a subset of CCs should be chosen if it fulfills the following formula:
S= arg max{Tgain
Load} (1)
where:
S is a chosen subset of CCs Tgain is a Throughput gain
Load is an overall Load
For the sake of simplicity it can be decided that RSRP level is the criteria for Primary CC selection. Additionally, in order to ensure system’s immunity to changing radio conditions and take the full advantage of the possibility to utilize multiple carriers, such ’CC allocation review’ should be executed periodically, every k TTI (k 1 ms, to avoid excessive signaling). Once it turns out it is beneficial to run such reassignment, SCCs are swapped. As a result - instantaneous load is mitigated and data rate opportunities are exploited [8]. The situation alters to a more complicated once we move towards Heterogeneous networks - a deployment type which rapidly becomes a reality. The co-existence of macro cells and dispersed layer of pico cells results in a serious challenge in terms of Radio Resource Management (RRM). One of the most significant differences between typical macro base station (BS) and pico BS is the output power. Macro BS will be capable of transmitting with 43 dBm - 46 dBm power level (i.e. 20 W - 30 W) whereas small cell BS usually has no more than 30 dBm (i.e. 1 W). The discrepancy is substantial and usually leads to a small cell under-utilization as the majority of users would anchor to the macro cell. It is obviously due to higher macro BS Rx power level, even in the relative vicinity of the small cell BS. In order to mitigate this undesired phenomenon
and increase the number of users off-loaded to a pico cell, a solution called Cell Range Expansion (CRE) is proposed. It simply relies on adding a positive bias (expressed in dBm) to pico cell RSRP measured by the UE. Such straightforward step yields an increased number of users scheduled by pico cell what is beneficial from interference point of view. A relative proximity of the UE to a pico BS may be exploited to apply a high order modulation (i.e. 256-QAM). Figure 2 de-picts a limited area of 256 QAM applicability. This modulation has very severe requirements with respect to SNIR (Signal-to-Noise-and-Interference-Ratio). Thus, it is foreseen 256-QAM will be predominantly used to transmit data to the UEs which are very close to the base station and simultaneously rather stationary than fast-moving.
Fig. 2. Limited area of 256 QAM applicability
In optimal conditions the usage of 256-QAM can boost spectral efficiency by 1/3 compared to 64-QAM scheme. 256-QAM is already in use in WLAN (i.e. in 802.11 ac standard) and has been specified in 3GPP Release 12. It implies it will be incorporated into LTE-A networks within the next few years. The proliferation of small cells will definitely serve as an incentive to introduce 256-QAM in DL.
Figure 2 illustrates also another mechanism which will be in-troduced in the near future due to Heterogeneous deployment. It is called ’Multi-site Carrier Aggregation’ and denotes a solution in which a single UE is capable of combining CCs originating from separate base stations (i.e. two different net-work points). Usually it would be a macro BS in conjunction with a pico BS. User should be able to utilize radio resources provided by two distinct schedulers, located in Master and Secondary eNBs (enhanced NodeB) [6]. Such approach im-plies serious challenges to be faced - especially with respect to C-plane and U-plane protocols and robust communication over X2 interface between engaged base stations.
Eventually, it is worth mentioning that in general there might be at least two approaches to RRM in Heterogeneous envi-ronment. The ’traditional’ one envisages the leading role of macro BS which is almost entirely responsible for resource management. Small cells are just informed what decisions have been made and are obliged to respect these. Nevertheless, resource coordination can be implemented in a different way. The proposal is to equip small cell base stations with an additional ’intelligence’. Each pico BS will be capable of ’neighbourhood sensing’ in order to gather interference related information about its surroundings. Carrier to Interference (C/I) ratio stored in a matrix will be a basis to decide which Component Carriers to use without causing detrimental effect
on neighbouring small cell BSs. Such approach is shown in Figure 3 and was described in [7].
Fig. 3. C/I matrix stores the results of neighbourhood sensing Certain CC will be chosen as a Secondary CC by BS #X only if current interference + SCC interference does not exceed the Threshold. Threshold is carefully determined in order to assure system fairness and cooperation between neighbouring sites. current interference denotes the network situation prior to assigning certain CC as a SCC whereas SCC interference is the additional interference brought on to the system by this certain CC.
III. CAIN H-RATS
Another step forward in network deployment is heteroge-neous Radio Access Technologies (h-RAT). As HetNets are based on different types of base stations within one RAT (for example LTE), the h-RAT utilize different radio technologies to enable network access. Most common example of h-RAT is LTE-A (3GPP Rel. 12) + WiFi (IEEE 802.11). CA can be also used in context of h-RATs, where terminals could be connected to LTE eNB as well as WiFi Access Point. Such approach is a great challenge due to some differences in physical layer and spectrum access. Table I gathers comparison of some key parameters of LTE and WiFi.
TABLE I
LTEANDWIFI COMPARISON
LTE WiFi
Frequency band licensed unlicensed Bandwidths 1.4, 3, 5, 10, 15, 20 MHz 5, 10, 20 MHz Spectrum access centrally coordinated distributed (CSMA) PHY layer OFDMA/SC-FDMA OFDM-CSMA
Co-existence of LTE and WiFi beside from increasing throughput for the LTE users can also introduce more reli-ability for the WiFi users which was lacking due to the fact WiFi is based on best-effort connection and cannot fulfill any QoS requirements. LTE, on the other hand, can assign time and frequency resources for specific users using Radio Resource Management algorithms and therefore can be dependable in terms of QoS.
Current research shows that aggregation of LTE and WiFi could be considered at different levels [10]:
a) radio access layer, using the same radio access (low layer - PHY/MAC)
b) core network layer
c) above IP layer (multiple connectivity)
As LTE is very strict in terms of resource allocations, mobility management, etc. one of the solutions is to allow the eNB coordinate process of aggregating carriers. Such approach was proposed in [11]. In order to allow CA in LTE+WiFi eNodeB must be aware that a WiFi AP is available in range. Discovery of the APs can be done either in the same way as it is done in pure WiFi infrastructure, where AP use request/report messages for collecting information about other APs in range [12] or the WiFi AP can be connected with eNB via wire (they can even be located in the same device). Successful detection should be followed by connection with each AP that will aggregate carriers. Protocol similar to X2 interface could be used to exchange messages about managing carriers between LTE eNB and WiFi AP. Initial results of LTE+WiFi have been also included in [9]. They have confirmed the assumptions that average rate per user is boosted with a joint usage of aforementioned two RATs. This gain becomes even more evident with the increasing number of users in the system (see Fig. 4).
Fig. 4. Average Rate per User in LTE + WiFi case [9]
Another example of h-RAT cooperation can be based on TV White Spaces (TVWS) exploitation. TVWS can offer addi-tional spectrum resources which can be used in conjunction with ordinary LTE allocations. However, this solution is highly location dependent as TVWS may be largely available in one geographical area whereas it can be virtually non-existent in another spot. In many areas such supplementary spectrum may be intensively occupied by primary users and therefore the likelihood of severe interferences rises. Thus, LTE + TVWS system should be described as ’opportunistic’ and ’best effort’. Taking it all into account, TVWS have to be utilized in compliance with the indications stored in geolocation database.
Fig. 5. Carrier Aggregation of LTE band and TVWS band [10]
Among other information, such data structure comprises chan-nel width and allowed power to be used in certain area. Figure 5 depicts such cooperation. Joint usage of LTE in ordinary Licensed spectrum and TVWS requires lots of attention also in case of RRM. Spectrum sensing has to be incorporated in order to determine transmission opportunities. Secondly, relatively narrow channels are accessible within TVWS (i.e. 6 MHz or 8 MHz). As a result, carriers up to 5 MHz can be used. Larger widths (i.e. 10 MHz, 15 MHz or 20 MHz) can be applied if contiguous TV channels are available and aggregated. The large unpredictability of TVWS can be exploited by higher-level application for mapping certain services to current spectrum opportunities. For example, services such as du-plex video-conferencing, which requires low delays and high certainty, may be mapped to a reliable, Licensed spectrum whereas applications such as chat or file transfer (i.e. low rate and not so susceptible to delays) will be intended for best-effort options such as TVWS [10].
IV. CONCLUSION
In this paper we have depicted Carrier Aggregation - a technique which undoubtedly will play a leading role in LTE enhancement process. Each 3GPP Release (from Release 10 onwards) contains a separate section on CA improvements what underlines the significance of this feature. As mentioned above, CA offers high flexibility to mobile operators by allowing them to combine scattered excerpts of bandwidth. Furthermore, due to larger transmission channel width, CA can address the emerging issue of rapidly growing traffic demand. On the other hand, a plethora of carrier aggregation distinc-tive opportunities implies additional difficulties to efficient resource management. Thus, profound studies are conducted (also as a part of SOLDER project) to create RRM algorithms which would effectively coordinate resources in diverse CA deployments. While it is relatively easy to incorporate CA into ordinary LTE/LTE-A networks, a smooth combination of CCs originating from LTE and TVWS or LTE and WiFi seems to be dubious. Particular research emphasis should be placed on the latter cooperation scenario due to omnipresence of WiFi. It is envisaged simultaneous data reception or transmission using both LTE and WiFi resources can fulfill the fast-paced growth of mobile traffic.
V. ACKNOWLEDGEMENTS
This work has been funded from DS-81-147-DSMK/2014/. REFERENCES
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