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Paradigm shifts with hetnets

  1. 1. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® TOPICS IN RADIO COMMUNICATIONS Seven Ways that HetNets Are a Cellular Paradigm Shift Jeffrey G. Andrews, University of Texas at Austin ABSTRACT if wireless (possibly to another wired-in BS), it must not be in the same spectrum used for com- Imagine a world with more base stations than munication with the mobile users; otherwise, cell phones: this is where cellular technology is such a device should be considered a relay. headed in 10–20 years. This mega-trend requires Relays may be useful in some cases for coverage many fundamental differences in visualizing, enhancement, but by reusing the same scarce modeling, analyzing, simulating, and designing “access” spectrum for backhaul, are inherently cellular networks vs. the current textbook inferior to BSs. And third, BSs need to have a approach. In this article, the most important sustainable power source. Usually, this is a tradi- shifts are distilled down to seven key factors, tional wired power connection, but it could in with the implications described and new models principle be solar, scavenging, wind-powered, and techniques proposed for some, while others fossil fuel generated (e.g., “mobile access points, are ripe areas for future exploration. APs” in vehicles), or something else. It may seem frivolous to define a ubiquitous INTRODUCTION technology that has existed for several decades. But it is important to recognize that traditional The global cellular communication network is tower-mounted BSs — what we call macrocells in one of electrical engineering’s crowning achieve- this article — are just a single type of BS, albeit ments, reliably connecting over half the planet’s the backbone that has enabled cellular’s success population, virtually everywhere where people to date. However, in many important markets, are. These networks — particularly in urban adding further macrocells is not viable due to areas — are in the midst of a paradigm shift as cost and the lack of available sites; for example, the number of base stations (BSs) increases many cities or neighborhood associations are rapidly each year, nearly all by virtue of small simply not very cooperative about opening up BSs (pico and especially femto) being added to new tower locations. The problem facing opera- the existing network. This unprecedented escala- tors is not coverage — which is now nearly uni- tion is due to intense consumer demand for versal — but capacity. There are just too many faster data connectivity, the impossibility of mobile users demanding too much data. meeting this demand by adding spectrum, and This will only worsen due to the continuing the increasing technical and financial viability of adoption of tablets, laptops with cellular connec- small BSs. By 2015, there will be perhaps 50 mil- tions, and smart phones along with their data- lion BSs [1], and some even predict that in the hungry applications. Adding BSs has been by far not too distant future, say 10–15 years out, the the most important factor historically for increas- number of BSs may actually exceed the number ing capacity. When BSs are added, each user of cell phone subscribers [2], resulting in a cloud- competes with an ever smaller number of users like “data shower” where a mobile device may for a BS’s bandwidth and backhaul connection: connect to multiple BSs, or at least frequently it may even have one or more BSs to itself. This have a BS to itself. How is this possible? What is the only scalable way to meet the current implications does such a scenario have on cellu- “capacity crunch.” Note that WiFi access points lar network design, wireless communications typically meet the above three criteria and are research, and the mobile computing industry? thus also BSs by our definition. WiFi is rapidly integrating with the cellular network, and roam- NOT YOUR PARENTS’ BASE STATION ing between cellular and WiFi will become Base stations are typically envisioned as big increasingly transparent to end users. Smart high-power towers or cell sites. And indeed, phones and tablets have sophisticated user inter- many are. Fundamentally, though, a BS must do faces and high-definition screens, expensive three things. First, it must be able to initiate and rechargeable batteries, substantial consumer accommodate spontaneous requests for commu- software, and support multiple wireless stan- nication channels with mobile users in its cover- dards. In short, there is no inescapable reason age area. Second, it must provide a reliable BSs needs to be more expensive than the phones backhaul connection into the core network. This they serve once they have lower transmit power connection often is, but need not be, wired, but (the power amplifier cost is considerably higher 136 0163-6804/13/$25.00 © 2013 IEEE IEEE Communications Magazine • March 2013C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  2. 2. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® Aspect Traditional Cellular HetNet Performance Outage/coverage probability distribution (in terms of SINR) Outage/coverage probability distribution (in terms of Metric or spectral efficiency (bps/Hz) rate) or area spectral efficiency (bps/Hz/m2) Nested cells (pico/femto) inside macrocells. BSs are BSs spaced out, have distinct coverage areas. Hexagonal Topology placed opportunistically and their locations are better grid is an ubiquitous model for BS locations. modeled as a random process. Cell Usually connect to strongest BS, or perhaps two strongest Connect to BS(s) able to provide the highest data rate, Association during soft handover rather than signal strength. Use biasing for small BSs. Downlink vs. Downlink and uplink to a given BS have approximately the Downlink and uplink can have very different SINRs; Uplink same SINR. The best DL BS is usually the best in UL too. should not necessarily use the same BS in each direction. Handoff to a stronger BS when entering its coverage area, Handoffs and dropped calls may be too frequent if use Mobility involves signaling over wired core network small cells when highly mobile, overhead a major concern. BSs often will not have high speed wired connections. BSs have heavy-duty wired backhaul, are connected into Backhaul BS to core network (backhaul) link is often the bottle- the core network. BS to MS connection is the bottleneck. neck in terms of performance and cost. Manage closed access interference through resource Employ (fractional) frequency reuse and/or simply tolerate Interference allocation; users may be “in” one cell while communicat- very poor cell edge rates. All BSs are available for connec- Management ing with a different BS; interference management hard tion, i.e. “open access” due to irregular backhaul and sheer number of BSs Table 1. Summary of the seven changes. in BSs, typically). Indeed, as of late 2012, an cell sizes, cell association should not be based iPhone costs about 10 times more than a typical just on signal strength or signal-to-interference- WiFi access point. Such trends will soon extend plus-noise ratio (SINR). Load is often more to femtocells and then picocells, in a dramatic important. reversal from a decade ago, when BSs cost about Uplink-downlink relationship. HetNets intro- 1000 times the mobile devices they served. duce a major asymmetry between the uplink and downlink, which affects several of the other IMPACT ON RESEARCH AND DESIGN items in this list. Cellular networks will thus be increasingly organ- The backhaul bottleneck. Placing BSs all over ic deployments of BSs of widely varying transmit the place is great for providing the mobile sta- powers (and hence coverage areas), carrier fre- tions high-speed access, but does this not just quencies, backhaul connection types, and com- pass the buck to the BSs, which must now some- munication protocols. A typical smart phone will how get this data to and from the wired core be capable of communicating via multiple bands network? over protocols including GSM/EDGE, code-divi- Mobility. How and when should users be ion multiple access (CDMA), Long Term Evolu- handed off between BSs when moving through a tion (LTE), WiFi, and perhaps other protocols, HetNet? Supporting mobility makes all the items and will make a choice based on what its needs in this list much more challenging. are (e.g., high-speed data or voice, or the amount Spectrum and interference management. of mobility) and a quick analysis of the available Nearly all of the above affect the nature of connections. interference in a HetNet. Furthermore, tradi- Needless to say, the implications of this trend tional methods of interference management like on the theory and implementation of cellular frequency reuse or BS coordination do not technology are extensive. This article organizes directly translate to HetNets. The above list is these changes into seven topics, which are subse- not exhaustive, nor are the items orthogonal to quently described in some detail, with a summa- each other; indeed, there is considerable over- ry given in Table 1. These are: lap. For example, managing mobility properly Metrics. Even the way we discuss and com- often boils down to appropriate cell association pare the performance of cellular systems needs choices. Nevertheless, this list captures the retooling. essence of how thinking must shift if we as engi- Network topology. Clearly, a heterogeneous neers are to make the most of this incredible network (HetNet) will have a very different opportunity. topology than a macrocell-only network. Since the distance to desired and interfering BSs is the first-order factor in determining performance, a METRICS reasonable topological model is required. We begin with the basic metrics used to rate the Cell association. How should users be associ- performance of a given cellular network. Natu- ated with cells as the network load fluctuates? rally, we must have meaningful metrics to mean- Because of massive differences between nominal ingfully compare different designs and IEEE Communications Magazine • March 2013 137C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  3. 3. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® Stop measuring performance with BER or SINR distribution, or with spectral efficiency. These metrics are no longer very relevant. Instead, use the rate distribution (user-perceived, i.e., accounting for load) or area spectral efficiency. Figure 1. Downlink (left) and uplink (right) Max-SINR association regions for a three-tier network with macros (red), picos (green), and femtos (black). Note that the BSs are in the same locations in these two plots, but the regions are very different. technologies. Two ubiquitous metrics are the academia and industry is the spectral efficien- outage/coverage probability and the spectral effi- cy, usually given in bits per second per Hertz ciency. of spectrum. This has always been a tricky The outage (equivalently one minus cover- metric for cellular, since the spectral efficien- age) probability is typically expressed in terms of cies vary so radically over the cell. For exam- the SINR cumulative distribution function (i.e., ple, in LTE-Advanced, peak downlink rates the probability that the SINR is below a particu- should allow a whopping 30 b/s/Hz, while the lar value). This maps to the probability that the cell edge requirement in the uplink is just bit error rate (BER) is above a corresponding 0.04 b/s/Hz: a nearly 1000 times difference. threshold, or the maximum instantaneous data Following similar logic, the spectral efficiency rate (at a target BER) is below one. What does distribution can be used to describe the spec- outage mean in a network with so many BSs tral efficiency statistics a BS observes, with operating over so many bands? The user experi- the average just being the expected value of ence depends on the application-level data rate this distribution. But this again neglects the achieved within a certain latency. What affects key consideration of congestion and load. A this, however, is not just SINR; the load can be better metric is area spectral efficiency, which considerably more important. normalizes by the cell area. For example, in The reason a HetNet requires a different an interference-limited environment (i.e., vir- viewpoint is that the law of large numbers tually any urban area), one can place four (LLN) — which more or less applies in a times more BSs with spacing R than with spac- macrocell-only network due to the large num- ing 2R. The spectral efficiencies would be the ber of users per cell — simply does not apply in same, but the area spectral efficiency of the a HetNet. When the LLN is applicable, the denser setup is four times higher, so the typi- SINR distribution provides a strong correlation cal throughput a mobile user could achieve is to the rate and/or quality of service (QoS) the also four times higher, assuming (optimistical- users will achieve. For example, the cell edge ly) that the mobiles and load are evenly spread users have lower SINR and hence lower rate; in space. interior users have higher SINR and higher As an example of a step in this direction, rate. In a HetNet, though, small BSs will often Third Generation Partnership Project (3GPP) be very lightly loaded, while others (the macro- Release 9 (see Technical Report 36.814, Sec. cells) will be very heavily loaded. Hence, the A.2.1.4 on System Performance Metrics) recom- congestion and load mostly determine the mends using a user-perceived throughput cumu- achieved rate. Most readers of this article will lative distributed function (CDF), and focuses know this to be true even anecdotally: their more generally on end-user throughput rather data rates and ability to use data-hungry appli- than SINR, BER, or spectral efficiency. Howev- cations screech to a halt in many cities at peak er, this important distinction seems to have been hours. A better definition of “outage” is the slow to migrate to the overall discourse about probability that no BS — or combination of cellular system performance, including industry BSs — can provide an aggregate data rate over more broadly and also in academia. some threshold. In a macrocell-only network, Recommendation: Stop measuring perfor- the metrics of SINR outage and rate outage mance with BER or SINR distribution, or with result in similar conclusions. In a small cell net- spectral efficiency. These metrics are no longer work, these two definitions of outage yield very very relevant. Instead, use the rate distribution different outcomes. (user-perceived, i.e., accounting for load) or area Another ubiquitous metric in both spectral efficiency. 138 IEEE Communications Magazine • March 2013C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  4. 4. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® TOPOLOGY An obvious change in a HetNet is the placement of base stations and their corresponding “cover- Wrap-around age” or association regions. Whereas macrocells contour are generally somewhat evenly spaced (although less so than widely believed), they have most commonly been modeled as lying on a lattice, in particular a hexagonal grid. The association regions are then simply the corresponding hexagons. Smaller base stations are not regularly spaced, nor are their association regions homo- geneous. Rather, they are scattered or clustered within the existing macrocell network and form their own embedded association regions, which are generally smaller, especially for the down- link, because the transmit power is significantly less. For example, typical macro, pico, and femto transmit powers are on the order of Pt = 40 W (effectively even higher due to high antenna gain), 2 W, and 100 mW. Thus, about an order of magnitude separates the transmit power of Pico cells each “tier” of base stations, and their nominal downlink association areas vary by about the same amount, as seen in Fig. 1. If a simple path loss model is used for average received power (i.e., Pr = Ptd–a), it can easily be shown that the Figure 2. The macro-pico model used by 3GPP in [3]. Other 3GPP models cell area increases as Pta/2, but it is in reality clos- include randomly located picocells inside the macrocell area. er to linear given that mounting heights and antenna gains are larger for higher-power BSs; thus, they have effectively larger coverage areas. On the other hand, the Poisson model is sur- prisingly tractable, and a large class of powerful SPATIAL MODELS FOR HETNET BASE STATIONS results and analytical tools are available from the The spatial modeling of the BS locations in a field of stochastic geometry [4]. Because of the HetNet remains an open topic, since little infor- presumed independence between BS locations, mation is yet available about picocell or femto- SINR distributions can be obtained in closed cell deployments. It does seem clear that the form even for networks with an arbitrary number grid-based models of the past are not scalable to of BS types: where each class of BSs is distin- an accurate model of a multitier HetNet, guished with different transmit powers, densities although one could construct a series of overlap- (i.e., average number of BSs per unit area), and ping grids of differing densities. For example, in SINR targets [5]. A high-level introduction and [3], macrocells are modeled with a hexagonal summary of the model and results in [5] are grid, with exactly six picocell BSs per macrocell, given in [6] and thus not repeated here. which are each located precisely on the bound- aries between neighboring BSs (Fig. 2). Needless INSIGHTS FROM THE POISSON MODEL to say, such a setup is highly idealized. In the The Poisson BS model is uncomfortable for absence of prior information, the best statistical many because of the independence assumption. model is a uniform distribution, which in the Clearly, BSs are not actually placed indepen- two-dimensional plane corresponds to a Poisson dently. Thus, alternative random distributions point process. Such a spatial distribution for BS that introduce an appropriate level of correla- locations corresponds to complete randomness, tion should be developed as more data becomes whereas the grid provides no randomness. Thus, available. What is important to recognize is that they are philosophically opposite, and any plau- there is little evidence that the Poisson model is sible HetNet BS deployment is bounded between any less accurate than the ubiquitous grid model, these two extremes. which is also very idealized. In fact, the two Although the relative merits of the determin- models give similar SINR distributions in terms istic and Poisson models are open to debate, one of shape, and differ mostly in terms of absolute important difference is that of tractability. SINR: with the grid model being optimistic (a Although the grid model is familiar, popular, best-case deployment for coverage) and the PPP and easy to conceptualize, it is not tractable. model being pessimistic (hard to do worse than Distributions on rate, SINR, and other metrics a purely random scattering of your BSs) [7], are found through detailed system-level simula- assuming the mobiles too are uniformly scat- tions that model nearby BSs as interference tered. sources, and typically ignore more distant BSs. The PPP model does, however, allow certain As small cells are added to the mix and the num- suspected “truths” to be confirmed mathemati- ber of “nearby” interferers grows, the complexity cally. Many of these truths are not widely known. of such simulations will also grow. Currently, the For example, it can be proven that once a net- simulation of interference in such networks and work is interference-limited, adding BSs of any the accurate determination of the SINR statistics type does not change the downlink SINR statis- under network dynamics is very time-intensive. tics, assuming any user can connect to the IEEE Communications Magazine • March 2013 139C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  5. 5. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® strongest one (i.e., open access), the network is Thus, these nominal coverage regions do not The downlink and fully loaded, and also interference-limited. This depend on UL power control (even though it further means that: too forms a major difference between DL and uplink need to be • The interference from new small cells is UL): at any transmit power, the closest BS will considered as two perfectly balanced by a decrease in the typi- allow the maximum received power on average. different networks, cal access distance to a nearby BS, and the Therefore, in a HetNet, the UL-DL relation- corresponding increase in desired signal ship is quite different than in a macro-only net- and will require dif- strength. work. For starters, a mobile may wish to be ferent models for • Adding BSs of any type strictly increases associated with different BSs in the UL and DL, capacity, since congestion is decreased and not doing so may be highly suboptimal. For interference, cell while SINR is constant. example, users toward the macrocell edges would association, and • Downlink power control is not terribly likely prefer to connect to a nearby picocell or throughput. important, since different power levels can femtocell, even if the corresponding signal is too be modeled as different types of BSs, which weak for DL reception. But if this is relaxed so Although this asym- from the above result do not affect the that the two directions become independent, metry existed in SINR distribution. there are interesting implications for the core These insights have been corroborated by network (traffic in each direction being routed macrocell only net- industry field trials and observations from to and from different BSs), and for the mobile’s works as well, the extremely detailed simulations. For example, QoS. For example, a mobile may be on the cell difference is poten- Qualcomm [8] observes that adding picocells to edge and have poor SINR in one direction but a macrocell network does not change the SINR not in the other. One saving grace that mitigates tially much larger in distribution and can only increase capacity (but this UL-DL imbalance is biasing, discussed in a HetNet. no reason or evidence is given). Drawing on the next section, which effectively increases Nokia Siemens’ field trials based on LTE Het- small-cell DL regions, making them more like Nets, [6] shows a high degree of agreement with the UL regions. the theoretical results of [5]. 3GPP also utilizes Additionally, the interference models and random small cell distributions for simulation resulting SINRs would be quite different in the models; for example, TR 36.814 randomly drops two links. Assuming orthogonal access (e.g., a fixed number (1, 2, 4, or 10) small cells inside orthogonal frequency-division multiple access, a larger macrocell area, and then assumes mobile OFDMA), users that are orthogonal to one user clustering around such cells. another on the downlink (sharing the same Recommendation: Phase out the grid model macrocell BS) may interfere with each other on for BS locations, which is neither tractable nor the UL if they are transmitting to different BSs. realistic for HetNets. Instead adopt a random Two-way channel models (e.g., classical interfer- spatial model for the BS locations. Poisson can ence channel models) that assume symmetry in be used for analysis, but more accurate distribu- the two directions are increasingly questionable. tions should be used for system-level simulations Many results in information theory based on (e.g. by the standards bodies). Such distributions UL-DL dualities are further eroded (interfer- need to be developed and validated by ence from other cells is already ignored to obtain researchers using actual BS deployment data. such results), because the channel gains and SINR in the two directions may be almost uncor- related, especially if they are via different BSs. UPLINK-DOWNLINK RELATIONSHIP Recommendation: The DL and UL need to The results in the last section focused on the be considered as two different networks, and will downlink. When thinking about a HetNet, it is require different models for interference, cell natural to think about macrocells having large association, and throughput. Although this asym- coverage areas, and pico and femtocells having metry exists in macrocell only networks as well, much smaller coverage areas. Indeed, because of the difference is potentially much larger in a the large transmit power disparities, a femtocell HetNet. coverage area might be limited to a single house, or even part of a single floor of a single building. This intuition does not extend to the uplink of the CELL ASSOCIATION network. This can be observed in the right side of In traditional cellular networks — and indeed, in Fig. 1: for the same BS locations, the downlink the prior two sections for multitier HetNets — and uplink max-power (and hence max-SINR) we typically assume that mobile users connect to coverage areas are very different. the strongest BS, which offers the best SINR. It is easy to understand why. In the uplink Assuming all BSs are fully loaded — transmitting (UL), all transmitters are roughly equal: they are and receiving packets in all their time-frequency mobile devices running off batteries. They all blocks at all times — such a strategy can easily have about the same transmit power and thus be shown to optimize sum throughput, where range: to a transmitting mobile device, a BS is each BS just communicates with its max-SINR just a receiver, and thus a femtocell and macro- user in each such block. Two obvious problems cell appear the same. Of course, macrocells may immediately emerge. First, maximizing sum-rate be tower-mounted and have higher-gain anten- is not a very practical objective, as cell-edge users nas (including receive antenna gain), while fem- will be ignored. However, even if all users are tocells may be indoors and have low-gain given an equal share of the resources (e.g., antennas. But these affects are about the same round-robin or proportional fair scheduling), it as in the downlink (DL), while the transmit still maximizes sum rate for each of them to con- power disparities between BS types in the DL nect to the strongest BS. However, in reality, the are 20 dB+, which is not the case in the UL. second and more important issue is that most 140 IEEE Communications Magazine • March 2013C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  6. 6. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® 1000 1000 900 BS14 Tier 3 900 BS14 Tier 3 800 BS15 Tier 3 800 BS15 Tier 3 BS9 700BS9 3 Tier 700 Tier 3 Tier 2 Tier 2 600 BS2 600 BS2 BS5 BS17 BS5 BS17 BS4 BS3 Tier 2 BS4 BS3 Tier 2 500 BS20 BS10 Tier 3 Tier 3 Tier 2 500 BS20 BS10 Tier 3 Tier 3 Tier 2 Tier 2 Tier 3 BS1 Tier 1 Tier 2 BS1 Tier 1 Tier 3 400 400 BS13 Tier 3 BS11 Tier 3 BS13 300 300 Tier 3 BS11 Tier 3 BS16 Tier 3 BS6 Tier 2 BS7 Tier 3 BS16 Tier 3 BS6 Tier 2 BS7 Tier 3 200 BS19 Tier 3 200 BS19 Tier 3 100 BS18 100 BS18 BS12 Tier 3 BS12 Tier 3 0 BS8 Tier 3 Tier 3 0 BS8 Tier 3 Tier 3 0 100 200 300 400 500 600 700 800 900 1000 0 100 200 300 400 500 600 700 800 900 1000 Figure 3. Base station associations in a three-tier HetNet using the traditional max SINR criteria (left) or a revised max sum log rate cri- teria (right). The right figure results in more balanced load and higher achieved data rates, especially for users who were previously on the macrocell edges. BSs — especially those with small coverage areas which are operating fairly near the Shannon and hence fewer active users — will not be fully limit in most cases, and it shows that significant loaded, and instead may be very lightly loaded. performance improvements are possible from In a macrocell-only network, the max-power load balancing. coverage regions for each BS are designed to Interestingly, a very simple suboptimal have roughly the same amount of traffic. That is, approach known as biasing, which is the pre- over time, more BSs are deployed in areas that ferred industry and 3GPP method of pushing generate more traffic, while sparsely populated load onto small cells, does nearly as well as a full areas get fewer. The law of large numbers is network-wide optimization. In biasing, small BSs applicable in such a network, so although the are preferred by some amount known as the bias traffic load certainly varies over space and time, value, to account for the fact that they are lightly it oscillates around a slowly varying value that is loaded. Then the usual max-SINR association is the sum of a large number of nearly uncorrelat- used with the biased SINRs. Referring to Fig. 4 ed traffic requests. Many small cells will have again, we see that (optimized) SINR bias values just a few users, so the LLN is not applicable, get very close to the network-wide optimum and the aggregate loads vary wildly from no load solution, which is fairly remarkable. The optimal at all to heavy load in times of sustained file SINR bias values vary depending on the network downloading or video streaming. An intelligent parameters, particularly the transmit power (and cell association policy should assign users to BSs thus coverage area) of each type of BS [9], and that offer them the best user-perceived rate. the density of the mobile users. Importantly, This rate will depend on both the SINR and the however, the optimum bias values do not strong- load; for example, the rate offered by BS i would ly depend on the number or density of such BSs, be approximately so the values may not need to be adjusted as the network topology changes or new BSs are added. B Ri = log 2 (1 + SINR i ) Recommendation: Initial work shows that Ki load balancing through cell range extension is very valuable in a HetNet, and that biasing is where Ki is the number of users currently being nearly optimum compared to a centralized opti- served by that BS. This can be visualized through mization, which is perhaps surprising. More Fig. 3, where a modified criterion for cell associ- work is needed to better understand how to ation is shown on the right, which is clearly optimize (and adapt) biasing for HetNets, partic- much more balanced. ularly under realistic loading models and diverse A challenge is that optimizing the rate for all types of traffic (e.g., balancing QoS for data, users is very complex, and results in an exhaus- voice over IP [VoIP], and video streaming). tive search over all possible pairings, which is NP hard. This is because the rates of all users are nominally coupled: by shifting a user onto a dif- THE BACKHAUL BOTTLENECK ferent BS, the rates for all users on those two Cellular engineers typically assume that the main BSs go up or down because of the change in design challenge is the air interface: the connec- load. This is not computable in finite time even tion between the mobile and the BS. The BS is for modest-sized cellular networks. However, assumed to have significant amounts of process- through various physical relaxations, our recent ing power and a high-speed backhaul connection work [9] was able to find a numerically com- that easily handles the data flowing to and from putable upper bound on the rate distribution the BS. WiFi users — that is, anyone reading and a distributed algorithm that nearly achieves this article — have long been aware that this is it. The rate gains are very large compared to not true, and that the wired connection behind max-SINR association, on the order of two times the WiFi access point is far more important than for “average” users and three times for cell edge the peak advertised speed of the WiFi devices. users, as seen in Fig. 4. This is really quite a Cellular is rapidly heading in this direction. large gain in the context of today’s systems, Start with femtocells: these are very similar to IEEE Communications Magazine • March 2013 141C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  7. 7. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® appears to have been implemented commercially 1 by Ubiquisys’s “smart cell” picocell. Such con- Max-SINR 0.9 Joint association tent can be updated periodically at a time of low Fraction-rounding backhaul load. The gain of such innovations on 0.8 Distributed algorithm network performance can be large, but are invis- SINR bias 0.7 Rate bias ible unless the backhaul bottleneck is included in the formulation. 0.6 Rate CDF 0.5 MOBILITY 0.4 The reliable support of mobile connections is one of the cellular network’s main achievements, 0.3 and why cellular providers are able to command 0.2 large subscription fees vs. other forms of tele- phony and data access. Ensuring reliable voice 0.1 and data support in view of the challenges raised 0 thus far is a difficult task compared to macro- 0.005 0.01 0.03 0.05 0.1 0.3 0.5 1 3 cell-only networks, in which mobility support was Rate (b/s/Hz) already far from trivial. First is the issue of when handoffs should occur. Referring again to Fig. 1, Figure 4. Rate complementary distribution function on a log scale. A very large envision a mobile user traveling through this net- rate gain is observed over a max-SINR association for users in the bottom 50 work. When should it hand off? If the user is percent (edge users). moving slowly — a pedestrian, for example — handing off to a picocell is almost surely justi- fied, and possibly to an open access femtocell if WiFi in terms of their range and deployment, the offline signaling support is sufficient and it is and often use the same backhaul connections as able to offer a high data rate (possibly allowing WiFi APs. Clearly, a 10 MHz LTE femtocell is the user to clear any download or upload queue often going to be limited in speed by a typical if it would otherwise be on a congested macro- cable modem or digital subscriber line (DSL) cell). On the other hand, a user traveling at connection, particularly in the UL. There is vehicular speeds would likely prefer to avoid probably little to be done about this from a cel- handoff into and then out of a small cell that it lular engineering point of view, other than to would only be in for a few seconds or less, given conservatively allocate resources, and for the BS the overhead (utilizing overloaded backhaul to be aware of the backhaul speed and latency links) and delays such handoffs incur. In 3GPP, (which will affect its ability to coordinate the minimum time of stay (MTS) defines a resource allocation or handoffs with other BSs). threshold of time spent on a given BS, below Picocells are more interesting since they are which a handoff should not be done. A nominal operator deployed and aim to provide a com- value for MTS is 1 s [3]. Recall also that DL and mercial grade experience, and thus require a UL assignments may be distinct or else highly high-quality backhaul connection. Many desir- asymmetric, and loads on each BS are also very able picocell locations (lampposts, building cor- important in the context of BS association, ners, etc.) do not have existing wired adding to the complexity of handoff decisions. connections, and installing and maintaining such Traveling through a small cell without hand- connections may be financially prohibitive. A off results in what we term the “unwelcome desirable alternative is a wireless solution that guest” problem. The mobile user that does not uses underutilized spectrum that is not useful for hand off causes very strong temporary interfer- the air interface. One example is to use millime- ence to the small cell (on the UL) while receiv- ter wave frequencies (e.g., 30–100 GHz) that are ing strong interference on the DL. This can be very difficult to deploy in a mobile network, but mitigated in OFDMA through an appropriate for pico to macro backhaul communication over resource allocation that is mobility-aware, for a fairly static channel, may soon be viable [10]. example, enhanced intercell interference coordi- Another example is to use unlicensed or white- nation (eICIC) with subframe blanking, as in space frequencies, although this may be less LTE [3]. Overall, the rate of failure for handoffs robust in some markets unless significant new in HetNets is bound to be higher than in a interference mitigation technologies are macro-only network, and this has been con- deployed. Significant industry activity is occur- firmed by 3GPP studies, which see failure rates ring in this space, including solutions from well as high as 60 percent in a macro-pico HetNet, funded startups like Fastback, Siklu, and BLiNQ, with the average failure rate about doubling vs. a as well as the established telecom giants. macro-only network. While the problem increas- Recommendation: From a research point of es overall with mobility, the ping-pong effect view, a shift is required that recognizes the (leaving and then re-entering the same cell) is importance of this bottleneck. For example, actually worse with low mobility [3]. One seem- massive multiple-input multiple-output (MIMO) ing paradox, however, is that at a fixed network solutions [11] may be very challenging in mobile load, adding picocells may improve mobility per- channels, but can be adapted (particularly at formance by reducing the load per BS, thus high frequencies) to the backhaul channel. reducing the overall interference and likelihood Another clever example is the idea of caching of handover failures. popular content such as video clips or other Recommendation: Network-level analysis, common downloads at the small cells [12], which simulation, and design of HetNets must account 142 IEEE Communications Magazine • March 2013C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  8. 8. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® for the suboptimal associations introduced by mobility. Improved mobility modeling, handover 10 optimization, and mobility-aware interference management are all challenging topics for future 9 work. 8 SPECTRUM AND INTERFERENCE MANAGEMENT 7 Managing interference is a major concern in any cellular network. As we saw previously, and con- 6 trary to popular belief, interference is not inher- ently a worse problem in a HetNet. True, there 5 are many more interfering sources, and they will usually be closer, but the desired BS is also clos- er, and these effects roughly cancel each other 4 out in a co-channel deployment. What is also true is that HetNets introduce some new chal- 3 lenges as far as managing and mitigating inter- ference, since a traditional macrocell method like static frequency reuse (or in GSM, time slot 2 averaging) is hard to implement and not terribly effective. Biased cell associations, which we have 1 seen are crucial for macrocell offload and for maximizing the overall network utility, place a further burden on interference management 0 since users are now communicating with BSs 0 1 2 3 4 5 6 7 8 9 10 other than their “home” BS, and thus subject to increased DL interference, as well as causing Figure 5. Power-based fractional frequency reuse in a realistic macrocell net- strong UL interference. work. Fortunately, OFDMA-based cellular systems provide significantly more flexibility and robust- ness than CDMA systems, which are single carri- increase in network throughput [14], or in a er and also sensitive to the near-far problem. In by-now notorious example, up to 1000 times if an OFDMA system, edge users can be assigned the scheme is renamed distributed-input dis- different time-frequency blocks than either edge tributed-output (DIDO) [15]. Such optimism users in adjacent cells or interior users in any does not appear to be very well supported by cell. This robust approach, which can be done the evidence, however. The Qualcomm HetNet semi-statically, is known as fractional frequency system design team, for example, found that reuse (FFR) and is shown visually in Fig. 5 for a after accounting for necessary overheads, the realistic macrocell deployment. Such an “gains” from CoMP in a HetNet were less approach can be extended to HetNets, although than 0 percent [16], while recent theoretical it is more complex, particularly as the number of results show that if channel uncertainty and tiers increases [13]. It can also be implemented background interference are brought into the in the time domain, which is known as eICIC in analysis, even the theoretical best case gains 3GPP. Another OFDMA-based approach could are much smaller than widely envisioned [17]. be to just have small cells use certain specific In short, coordinating small cell transmissions subbands that are distinct from the macrocells, is much less important than just maximizing and for the macrocells to not use those bands the sheer volume of small cell deployments, for highly mobile users (to avoid the unwelcome and providing efficient load balancing via guest problem). A further possibility is carrier biased cell associations. aggregation, whereby mobile users may use sev- Recommendation: Efficient interference man- eral bands simultaneously, possibly over differ- agement in a HetNet relies on reasonable mod- ent tiers, with the band allocation varying els for all the previous topics discussed until geographically and in time depending on the now, and can be seen as encompassing key traffic pattern. In general, using different bands aspects from the previous six sections (e.g. biased for different tiers (e.g., 800 MHz for macrocell cell associations, random network topologies, and 2.5 GHz for picocells) is suboptimal from a mobility, and UL-DL asymmetry). Ignoring throughput standpoint. these crucial issues will usually result in mislead- There is considerable optimism that coordi- ing conclusions regarding interference. nated multipoint (CoMP), alternatively known as network MIMO or BS cooperation, is an impor- tant aspect for HetNet interference suppression. CONCLUSIONS The main idea behind CoMP is to have neigh- The rapid trend toward extreme heterogeneity in boring BSs cooperatively encode (DL) and mobile communication networks requires many decode (UL) messages for multiple simultaneous longstanding models and the associated conven- users, thus getting a multiplexing gain vs. treat- tional wisdom to be reevaluated. This trend is ing them as interference. Some theoretical irreversible, and will have a profound impact on and/or numerical results predict a several-fold both the theory and practice of communication IEEE Communications Magazine • March 2013 143C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®
  9. 9. C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND® systems. In this article, we have attempted to [13] T. D. Novlan et al., “Analytical Evaluation of Fractional Frequency Reuse for Heterogeneous Cellular Networks,” The rapid trend highlight some of the changes required, both IEEE Trans. Commun., vol. 60, no. 7, July 2012, pp. from a design and implementation perspective 2029–39. towards extreme (many of which are well underway in industry [14] G. J. Foschini, K. Karakayali, and R. A. Valenzuela, heterogeneity in already), and in basic research, where this “Enormous Spectral Efficiency of Isolated Multiple Antenna Links Emerges in A Coordinated Cellular Net- mobile communica- paradigm shift seems to be less appreciated. work,” IEE Proc. Commun., vol. 153, no. 4, Aug. 2006, pp. 548–55. tion networks ACKNOWLEDGMENTS [15] S. Perlman and A. Forenza, “Distributed-Input-Dis- The author appreciates feedback and input from tributed-Output (DIDO) Wireless Technology: A New requires many long- Approach to Multiuser Wireless,” Rearden White Paper, Arunabha Ghosh, Angel Lozano, Kevin Negus, July 2011. standing models and Harpreet Dhillon, Xingqin Lin, and Qiaoyang [16] A. Barbieri et al., “Coordinate Downlink Multi-Point the associated con- Ye. He also appreciated several very helpful Communications in Heterogeneous 4G Cellular Net- comments from the reviewers. works,” Info.Theory and Applications Wksp. (ITA), Feb. ventional wisdom to 2012. [17] A. Lozano, R. W. Heath, and J. G. Andrews, “Funda- be reevaluated. This REFERENCES mental Limits of Cooperation,” submitted to IEEE Trans. trend is irreversible, Info. Theory, vol. http://arxiv.org/abs/1204.0011, 2012. [1] J. G. Andrews et al., “Femtocells: Past, Present, and Future,” IEEE JSAC, Apr. 2012. and will have pro- [2] D. P. Malladi, “Heterogeneous Networks in 3G and 4G,” BIOGRAPHY found impact on IEEE Commun. Theory Wksp., http://www.ieeectw.org/ program.html, May 2012. _______ JEFFREY ANDREWS [S’98, M’02, SM’06, F’13] (jandrews@ece. ________ both the theory and [3] 3GPP TR 36.839 v11.0.0, “Mobility Enhancements in utexas.edu) received his B.S. in engineering with High Dis- ______ Heterogeneous Networks (Release 11),” Sept. 2012. tinction from Harvey Mudd College in 1995, and his M.S. practice of commu- [4] M. Haenggi, Stochastic Geometry for Wireless Net- and Ph.D. in electrical engineering from Stanford University works, Cambridge Univ. Press, 2012. in 1999 and 2002, respectively. He is a professor in the nication systems. [5] H. S. Dhillon et al., “Modeling and Analysis of k-Tier Department of Electrical and Computer Engineering at the Downlink Heterogeneous Cellular Networks,” IEEE JSAC, University of Texas at Austin (UT Austin), where he was the Apr. 2012. director of the Wireless Networking and Communications [6] A. Ghosh et al., “Heterogeneous Cellular Networks: Group from 2008 to 2012. He developed CDMA systems at From Theory to Practice,” IEEE Commun. Mag., June Qualcomm from 1995 to 1997, and has consulted for enti- 2012. ties including the WiMAX Forum, Intel, Microsoft, Apple, [7] J. G. Andrews, F. Baccelli, and R. K. Ganti, “A Tractable Clearwire, Palm, Sprint, ADC, and NASA. He is co-author of Approach to Coverage and Rate in Cellular Networks,” two books, Fundamentals of WiMAX (Prentice-Hall, 2007) IEEE Trans. Commun., vol. 59, no. 11, Nov. 2011, pp. and Fundamentals of LTE (Prentice-Hall, 2010), and holds 3122–34. the Earl and Margaret Brasfield Endowed Fellowship in [8] A. Damnjanovic et al., “A Survey on 3GPP Heteroge- Engineering at UT Austin, where he received the ECE neous Networks,” IEEE Wireless Commun., vol. 18, no. Department’s first annual High Gain award for excellence 3, June 2011, pp. 10–21. in research. He is a Distinguished Lecturer for the IEEE [9] Q. Ye et al., “User Association for Load Balancing in Vehicular Technology Society, served as an Associate Editor Heterogeneous Cellular Networks,” IEEE Trans. Wire- for IEEE Transactions on Wireless Communications from less., http://arxiv.org/abs/1205.2833, to appear. 2004to 2008, was Chair of the 2010 IEEE Communication [10] Z. Pi and F. Khan, “An Introduction to Millimeter-Wave Theory Workshop, was Technical Program Co-Chair of ICC Mobile Broadband Systems,” IEEE Commun. Mag., vol. 2012 (Commuications Theory Symposium), and holds the 49, no. 6, June 2011, pp. 101–07. same position for IEEE GLOBECOM 2014. He received the [11] T. Marzetta, “Noncooperative Cellular Wireless with National Science Foundation CAREER award in 2007 and Unlimited Numbers of Base Station Antennas,” IEEE has been co-author of five best paper award recipients, Trans. Wireless Commun., vol. 9, no. 11, Nov. 2010, two at IEEE GLOBECOM (2006 and 2009), Asilomar (2008), pp. 3590–600. the 2010 IEEE Communications Society Best Tutorial Paper [12] N. Golrezaei et al., “Femtocaching: Wireless Video Award, and the 2011 Communications Society Heinrich Content Delivery Through Distributed Caching Helpers,” Hertz Prize. He is an elected member of the Board of Gov- http://arxiv.org/abs/1109.4179, 2011. ernors of the IEEE Information Theory Society. 144 IEEE Communications Magazine • March 2013C qM IEEE M ommunications q qM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page MqM q Qmags THE WORLD’S NEWSSTAND®

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