Smart and flexible antenna hardware provides a step in the right direction for spectrum efficiency, channel loading and reliability.
Data is the buzzword du jour on the lips of just about everyone in the wireless industry. And certainly ample reason exists to believe that non-voice traffic will play an increasingly large role in defining the technology, business opportunities and challenges of the wireless future.
What is often overlooked in the enthusiasm to gaze over the data horizon, however, is that growth in voice subscriber numbers and minutes of use shows little sign of slowing. While the impact of the data explosion on carriers' networks remains largely hypothetical, the challenge of providing sufficient network capacity to handle current (mainly voice) traffic is already a daunting reality for many operators. Whether one focuses on the impending demands of data traffic or the needs of more than 60 million current CDMA subscribers in the here and now, the issue of how to increase network capacity in a cost-effective, scalable manner is pivotal.
Among other approaches to this problem, six-sector cells and smart antennas are two ideas that have generated a great deal of interest among network operators. Smart antenna technology can facilitate the successful implementation of six-sector in CDMA networks.
Six-sector theory and practice
In theory, increasing the number of sectors in a CDMA cell is a good way to increase its capacity. Everything else being equal, a six-sector cell should offer double the capacity of a three-sector cell with a similar coverage footprint.
Unfortunately, everything else is not equal. As the number of sectors increases, the total area of the softer handoff zones between sectors increases, which in turn increases the “handoff overhead” of the cell. And because mobiles in softer handoff require downlink transmit power from more than one sector at a time, handoff overhead exacts a direct cost in terms of cell capacity.
Similarly, the more sectors there are, the greater the likelihood of pilot pollution. As the number of strong pilots in any locale increases, the noise floor rises with a direct and negative impact on capacity. Thus, while increasing the sectorization of a cell increases capacity in some ways, it decreases it in others. In practice, cells with more than three sectors have generally not offered anywhere near the expected capacity payoff.
Implementing six-sector with conventional antennas has typically entailed serious challenges. The sheer number of separate antennas required for a six-sector deployment means that the physical installation and alignment processes are painstaking and expensive. Iterative tower climbs are the order of the day in optimizing a conventional six-sector site, and that's only after the ever-more-difficult zoning battles have been waged and won.
The smart antenna six-sector solution
Smart antenna systems make six-sector a practical proposition. They do so in three principal ways: by reducing handoff overhead, by easing the implementation burden and by facilitating successful optimization.
The size of the softer handoff zones between sectors in a CDMA cell is a function of the rolloff characteristics of the antennas employed. The sharper the main-lobe rolloff, the smaller the areas of overlap between sectors where mobiles will be in softer handoff. The software-defined sector patterns produced by the phased-array panel antennas of a smart antenna system display much sharper rolloff than do conventional antennas — so much sharper that the handoff overhead of a six-sector cell equipped with smart antennas can be roughly comparable to that of a typical three-sector site with conventional antennas. This means that the theoretical capacity gains offered by the additional sectors can actually be practically realized with smart antennas.
Smart antenna systems ease the implementation burden of six-sector deployments by reducing the number of antennas required on the tower. With conventional antennas, six-sector can require as many as 18 precisely aligned antennas for the site to operate properly. With a smart antenna system, as few as three antennas do the job, regardless of whether the site is configured for three, four, five or six sectors.
Smart antenna systems can significantly reduce the amount of additional equipment necessary to implement six-sector. Of course, six-sector requires two base station radios, but with conventional antennas, it also requires twice the power amplifiers, duplexers, filters and cabling compared to three-sector. Because a smart antenna system manages the RF signal flow from the base stations all the way to the antennas, no additional amplifiers, duplexers, filters or cabling is required. This results in significant cost savings. Figures 1 and 2 illustrate the reduction in equipment that a smart antenna system makes possible.
Finally, smart antennas make six-sector optimization easier. Through remote software control, network engineers can manipulate the gain and phase of each individual narrow beam comprising the smart antenna pattern. This “sculpts” the coverage footprint to manage pilot pollution and control the location of handoff regions. Compared with the precision and flexibility inherent in smart antenna systems, conventional antennas afford only the crudest control over these critical parameters. Smart antennas allow six-sector to be successfully deployed in sites where optimization issues would prevent it with conventional antennas.
The recent commercial deployment of a CDMA smart antenna system in multi-sector configurations was implemented in a case study. Examining the deployment illustrates many of the advantages smart antennas have to offer. The deployment had four objectives:
To demonstrate the ease and cost-effectiveness of deploying multi-sector with smart antennas.
To significantly increase the capacity of the cell over the three-sector baseline, and to quantify this increase.
To maintain or enhance quality of service relative to the three-sector baseline, not only in the case-study cell but in neighboring cells.
To demonstrate the unique ability afforded by smart antennas to reconfigure a cell from four- to five- to six-sector through software control.
The cell where the deployment occurred is a busy suburban site in the network of a major U.S. cellular operator. The site was originally configured in three-sector using conventional antennas and a Nortel Networks CDMA Metro Cell base station.
The site was configured with two CDMA carriers. Rather than employing a hashing algorithm to allocate traffic between the two carriers, the operator implemented an overflow algorithm that directs traffic to the second carrier (F2) only when the first (F1) reaches its capacity limit. This feature provided a convenient method for measuring the capacity improvement provided by the smart antenna deployment.
Baseline switch statistics showed that traffic was distributed relatively equally among the three original sectors of the cell, with the alpha, beta and gamma sectors carrying on average 32%, 39% and 29% of the total load, respectively. As each sector of a perfectly balanced cell would carry 33.3% of the load, the “peak load” in the beta sector can be expressed as being about 117% of “ideal.” This figure represents more balanced loading than is often observed in commercial CDMA cell sites. Experience in using smart antennas to generate custom sector patterns (to balance traffic loading in three-sector sites) suggests that load balancing renders significant capacity benefits when peak loading is greater than 120%. Cells like this one, in which the absolute traffic load is high and evenly distributed, are ideal candidates for the six-sector solution.
Prior to system installation, the RF footprint of the cell was determined empirically with CDMA drive-test equipment. Figure 3 shows the plot of the strongest serving pilot PN offset for the baseline configuration. Subsequently, a smart antenna system was installed, and commercial traffic was cut over to the system initially in a three-sector configuration that duplicated the sector orientation and coverage of the baseline configuration. Then, after installation of a second Metro Cell base station, the site was taken to six-sector. Before and after ERP plots of the two configurations are shown in Figure 4. The footprint of the six-sector pattern was also verified through drive-testing; the six-sector strongest serving pilot PN offset plot is shown in Figure 5.
Four- and five-sector configurations were also implemented and measured in commercial service. All sectorization changes after the initial cut-over to the smart antenna system were implemented through remote software control of the beamwidth, azimuth pointing angle and per-beam gain of the synthesized antenna patterns. No physical changes to the antenna tower were required.
Measuring capacity gain
Measuring the capacity of a CDMA cell site is not straightforward. Therefore, it is typically difficult to quantify the precise capacity improvement attributable to a configuration change. However, the way the operator of this network implemented F2 provides a convenient means of estimating capacity gain in this instance.
Users are assigned to F2 only after traffic on F1 causes the base station to exceed an operator-established threshold of 67% of maximum transmit power. Thus, any call completions on F2 can be considered as having been blocked on F1. The probability of a call being blocked can be expressed as the grade of service (GOS), which can be calculated for this cell from switch statistics by:
where TF1 and TF2 are the number of call completions over a given time on F1 and F2, respectively. For any given level of traffic, therefore, a low GOS indicates that F1 is carrying most traffic and that relatively little blocking would be present if F2 were absent; a high GOS indicates that a high level of blocking would occur without F2.
To assess the efficiency of the cell under different sectorization schemes, the observed GOS can be plotted against call completions. An efficiency curve can then be computed using the Erlang B model that best fits the observed data. The general Erlang B model is given by:
where C is the number of trunked channels offered by a trunked radio system and A is the total offered traffic in Erlangs. In determining the best-fit curve, the value of C is chosen to minimize the squared error between the observed GOS at a given level of traffic and the predicted GOS from the model for the same level of traffic. Offered traffic, A, is taken to be the number of call completions in a given hour (TF1 + TF2) multiplied by a constant representing assumed average call duration.
The Erlang B model does assume a fixed-trunk air interface, and CDMA does not strictly meet this criterion either. This is because the number of available channel elements varies with the forward-link power requirements and the handoff state of the mobiles being served. However, over time, there is an average number of “available” channel elements, and thus the Erlang B model still provides a good approximation of GOS for a CDMA cell.
The results of the analysis are presented in Figures 6 and 7. Figure 6 shows the best-fit Erlang B curves relating GOS to offered traffic for the baseline three-sector and smart antenna six-sector configurations using data from the 4 p.m to 5 p.m. busy hour. It is appropriate to concentrate on the busy hour because this is when any capacity gains afforded by six-sector will be most valuable to the network operator — in terms of network efficiency and revenue. Data were collected over 15 consecutive days for the baseline configuration and over 12 consecutive days for the six-sector configuration.
Figure 6 shows that the smart antenna six-sector configuration resulted in a significant rightward shift in the best-fit curve. This indicates that, at a given GOS, the six-sector cell was carrying more offered traffic. Figure 7 presents the magnitude of this increase at various grades of service. At a reasonable 2% GOS (i.e., a 2% access failure rate), the smart antenna system in six-sector increases capacity by 73.6%.
This significant increase in cell capacity can be attributed to the control of handoff overhead. Figure 8 compares Ec/I0 plots for the baseline three-sector configuration with conventional antennas and the smart antenna six-sector configuration. The size of the inter-sector softer handoff regions — and thus the amount of handoff overhead — is indicated by the darker shaded areas. By inspection, the amount of handoff overhead appears roughly equivalent between the two configurations. In fact, as measured by the ratio of Walsh-code Erlangs to primary Erlangs, handoff overhead increased less than 7% in moving from the three-sector baseline to the six-sector configuration (1.86 to 1.99), despite the 100% increase in the number of handoff zones. This means that, in contrast to the conventional six-sector case, scarcely any of the capacity gains of a six-sector deployment facilitated by smart antennas are squandered on unproductive overhead; they are instead available to carry revenue-producing traffic.
Quality of service
The main purpose of the six-sector deployment was to provide increased site capacity. Metawave's smart antenna system delivered on that promise. But capacity gain in any single cell would not be worthwhile if it came at the expense of quality of service (QoS) in the cell itself or in neighboring cells. The case study results show that, overall, the smart antenna deployment maintained, and in some ways actually enhanced, the performance of the study cell and its neighbors.
To make meaningful QoS comparisons, it is necessary to establish that the levels of carried traffic before and after the implementation of the smart antenna system are roughly comparable. The switch data on call completions presented in Table 1 demonstrate that this was the case; both in the study cell and its neighbors.
Typically, six-sector deployments using conventional antennas suffer QoS problems due to excess pilot pollution. In areas where a dominant server does not exist because of pilot pollution, one would expect significant problems with dropped calls and access failures. As Table 2 shows, the smart antenna six-sector deployment belied these expectations. The dropped call rate fell by between 10% and 55% in every cell in the cluster. With regard to access failures, three cells experienced slight increases (of between roughly 1% and 7%), while two others experienced decreases of almost 20%. On balance, the smart antenna system in six-sector delivered enhanced QoS along with greater capacity.
A final goal of the deployment was to demonstrate the flexibility of smart antenna systems in reconfiguring a site from one sectorization scheme to another through software control. Flexible smart antenna technology makes it practical for an operator to take a three-sector antenna site to a four-, five-, or six-sector site and back again as traffic and RF demands change. As an example of the real-world uses of this feature, imagine implementing a three-sector smart antenna solution to balance traffic loading in a highly imbalanced cell. A year later, after a new shopping mall, freeway and housing development have appeared within the footprint of the cell, one might conclude that the heavy loading across all three sectors indicated a six-sector solution. And a year after that, one might decide to take the site back to four sectors to help manage pilot pollution arising from a new neighboring off-load site. Smart antennas can provide the flexibility to make such changes with minimal base-station equipment changes and with no changes whatsoever to the antennas on the tower.
|Configuration||Estimated capacity |
increase @2%GOS (%)
|Average daily dropped |
call rate (%)
|Average daily access |
failure rate (%)
As a demonstration of this flexibility, the study site was operated for five days each in four- and five-sector configurations. The estimated capacity increases, dropped call rates and blocking rates for these two configurations relative to the baseline three-sector configuration are presented in Table 3.
Because the goal of this deployment, relative to the four- and five-sector configurations, was to demonstrate how smart antennas enable easy, software-controlled sectorization changes, neither configuration was optimized in any systematic way. Both the four- and five-sector configurations feature beamwidths large enough to provide real scope for traffic load balancing using the smart antenna system's ability to adjust beamwidth and orientation, as in the well-proven three-sector case. One could expect this effort to produce incremental capacity gains beyond those reported in Table 3, as those gains resulted entirely from the increased number of sectors.
The results of this deployment provide conclusive validation of the use of smart antennas to facilitate multiple sectorization schemes in CDMA cells. The sharp sector rolloff characteristics of such systems' software-defined, multi-beam antennas produce in practice the substantial capacity benefits that four-, five- and six-sector configurations have long promised in theory. In addition, the precision and flexibility of smart antennas allow operators to successfully negotiate the challenges of optimization in a way that conventional antennas do not.
No single sectorization scheme will prove optimal for every capacity-constrained CDMA cell. In many instances, the apparent capacity problem stems less from an absolute shortage of site capacity than from the uneven distribution of traffic among sectors. In such cases, using smart antennas to balance traffic loading by customizing sector size and orientation can “unlock” capacity that is sitting idle in under-utilized sectors. This can boost site capacity by as much as 50%, (as demonstrated by commercial three-sector deployments) without exacerbating problems of pilot pollution or neighbor list planning.
However, in cells where the traffic load is well-balanced among the three sectors — and balanced at an unacceptably high level — a six-sector configuration facilitated by smart antennas can create new capacity. In intermediate cases, smart antennas can both create additional sectors for greater capacity and distribute traffic more evenly across those sectors to boost site efficiency.
As subscriber numbers continue to soar, and as the predicted demand for data traffic begins to materialize, CDMA network operators will need to use all available tools and strategies to meet the attendant capacity challenges. Smart antennas will certainly be among the most flexible and cost-effective of those tools, and using such systems to facilitate flexible, multiple sectorization schemes will likely be among the most promising strategies.
About the author
Ji-Hae Yea is currently senior RF network Engineer at Metawave Communications. Yea has led numerous projects on smart antenna field trials and deployments and is a member of multiple project core teams for smart antenna system design and product development. His current areas of interest include algorithm development, wireless position location and performance analysis for wireless voice and high-speed data systems. He holds a Bachelor of Science in Electronics from Dankook University, Korea, and a Master of Science in Electrical Engineering from the University of Washington. He can be reached at 888.638.2928 or through the company's Web site at: www.metawave.com .