Wireless communications systems use adaptive smart antenna technology: Optimal exploitation of the spatial dimension may meet the growing need of wireless system operators for improvements in coverage, capacity and quality within their communications netw
Wireless communications is widely recognized as one of the fastest-growing industries. As with any nascent industry faced with an unexpectedly large demand for products, growing pains are inevitable. System providers are pressed to expand their suite of services and to provide them at ever-decreasing costs. Unfortunately, there is only so much product to sell, and technological limitations are in many instances becoming significant barriers to satisfying consumers’ demands. The following information describes some current technical challenges facing wireless service providers, historical attempts to address these challenges and how adaptive smart antenna technology may be helpful.
Wireless ‘objective’ With respect to most currently deployed wireless telecommunication systems, the objective is to sell a product at a fair price_the product being information transmission from one or more points to one or more other points. Cellular and next-generation personal communications services (PCS) systems, in some sense the “killer apps” of wireless, are classic examples in which operators sell point-to-point information transfer to consumers largely in the form of circuit-switched (voice) links over which standard phone calls can be placed.
From a technical standpoint, information transmission requires resources in the form of power and bandwidth. Generally, increased transmission rates require increased power, bandwidth or both_independent of the medium.
Although transmission over wired segments of the links generally can be performed independently for each link, (ignoring crosstalk in landlines), this is not the case for wireless segments. Although wires (fibers) are excellent at confining most of the useful information or energy to a small region in space (the wire), wireless transmission is much less efficient.
Reliable transmission over relatively short distances requires a large amount of transmitted energy, spread over large regions of space_only a small portion of which is actually received by the intended user. Most of the energy often is considered to be interference to other potential users of the system.
Somewhat simplistically, the maximum wireless system range largely is determined by the amount of power that can be transmitted (and therefore received), and capacity largely is determined by the amount of spectrum (bandwidth) available. For a given amount of power (constrained by regulation or practical considerations) and a fixed amount of bandwidth (the amount operators can afford to buy at auction these days), there is a finite (small) amount of capacity (bits/sec/Hz/unit-area, really per unit-volume) that operators can sell to their customers, and a limited range over which customers can be served from any given location. Thus, two basic challenges arise in such systems:
how to acquire more capacity so that a larger number of customers can be served at lower costs in areas where demand is high. how to obtain greater coverage areas to reduce infrastructure site development and maintenance costs in areas where demand is relatively low.
Quest for capacity In areas where demand for service exceeds the supply, the real game being played is the quest for capacity. Unfortunately, to date, a universal definition of capacity has not emerged. Free to make their own definitions, operators and consumers have done so. To consumers, it is quite clear that capacity is measured in the quality of each link they get and the number of times they can successfully get such a link when they want one. Consumers want the highest-possible-quality links at the lowest-possible cost.
Operators, on the other hand, have their own definition of capacity in which great importance is placed on the number of links that can be established simultaneously. Because the quality and number of simultaneous links are inversely related in a resource constrained environment, operators lean toward providing the lowest-acceptable-quality links to the largest possible number of users. That the conflict continues is evidenced by churn and the lack of acceptance of current digital systems in markets where competitive analog service is available. Consumers’ desire for better links is constantly at odds with operators’ drive to maximize profitability by providing an increasing number of lower-quality links at the highest acceptable price. Until the quest for real capacity is successful, the battle between operators and their customers over capacity_the precious commodity that operators sell to consumers_will continue.
Attempts to increase marketable capacity center on transitions to digital systems. Unfortunately, this approach has involved giving less capacity to each customer (through voice compression). Consumers, having long associated digital technology with superior performance at lower cost, are largely disappointed with digital wireless performance and cost. Attempts at increasing system capacity have involved the development of sectorized antennas for cellular systems, culminating with the more recent attempts to develop cost-effective microcellular concepts. Such systems suffer from trunking inefficiencies and higher costs per line, but they can represent ways of increasing capacity where the costs can be justified. As a long-term solution, though, providing base stations everywhere to service everyone may not be economically viable.
Requirements for long range There are many situations where coverage, not capacity, is more important. Consider the roll-out of any new service such as PCS. Prior to initiating service, capacity is no problem_operators have no customers. Until a significant percentage of the service area is covered, service can not begin. Clearly, coverage is important during the initial phases of system deployment.
In many instances, only an extremely small percentage of the area to be served is heavily populated. Furthermore, the degree to which customers in those areas can be enticed to subscribe is a function of the coverage provided by the operator in the other “99.9%” of the service area. The ability to cover the service area with a minimum investment in infrastructure is important in keeping costs down and customers happy.
As is often painfully obvious to operators, the two requirements, increased capacity and increased range, conflict in most instances. Although current technology sometimes can provide increased range and, up to a limit, increased capacity, it rarely can provide both simultaneously. Operators that want to keep infrastructure costs low by deploying fewer sites must sacrifice revenue-generating capacity, and those that opt for more capacity must pay the price. Intelligent antenna technology offers the potential to ease the pain by providing the capability to increase coverage and capacity at the same time and, more importantly, by providing the flexibility to adjust to the particular needs of the operator as the system requirements evolve.
Space: ‘the final frontier’ Space is truly one of the final frontiers when it comes to next-generation wireless communication systems. Spatially selective transmission and reception of RF energy promises substantial increases in wireless system capacity, coverage and quality_as attested to by the number of companies that have been formed to make wireless products based on such concepts. The approaches range from switched-beam to fully adaptive, uplink-only to uplink and downlink, each with different advantages. As one of Qualcomm’s founders, Andrew Viterbi, Ph.D., said: “Spatial processing remains as the most promising, if not the last frontier, in the evolution of multiple access systems.”
Switched-diversity technology One of the first attempts to address the difficulties of the mobile RF environment was to use two identical antennas separated by several wavelengths (space diversity), each equipped with conventional receivers. The basic principle underlying such designs is that in complex RF environments, RF fields scatter enough to practically decorrelate signals received from antennas spaced adequately. The probability of signals in both of the antennas becoming extremely weak at the same time is small, and selecting the strongest signal always improves matters. Although these techniques remain in widespread use, they do not increase range or capacity, though they do address the important mobile system problem of fading (uplink signal quality) in complex RF (dense urban) environments.
Switched-beam technology As an extension of the microcellular concept, several companies are investigating switched-beam technology to improve range and capacity. The design of such systems involves high-gain, narrow azimuthal beamwidth antenna elements (using conventional or Butler matrix array technology) and RF or baseband digital signal processing (DSP) hardware and software to select which beam or sector to use. To overcome the well-known trunking efficiency problem of small cells, several proponents are investigating the pooling of radio resources. Additionally, many system-related issues connected with access and control channels require some special care, and interesting challenges are to be faced concerning the downlink in such systems. Even though previous unsuccessful attempts at such solutions date back to the 1970s when six-sectored systems were tested as improvements over three-sector technology, advances in DSP technology may enable more complex solutions to the problems created by highly restricted fields-of-view in rapidly changing mobile environments.
Adaptive smart antenna technology At the other end of the spectrum are adaptive smart antennas that use antenna arrays; standard RF and digital components; and spatial signal-processing techniques to increase the capacity and quality of many wireless communication systems. They are well-suited to current and next-generation cellular systems (PCS and wireless local loop [WLL] systems).
Antenna arrays coupled with adaptive digital signal processing techniques are used primarily at base stations to improve coverage, capacity and trunking efficiency, allowing lower-cost deployments with reduced maintenance expense. The technology’s flexibility allows for the creation of new value-added products and services that can give operators a significant competitive advantage. Adaptive smart antennas are not restricted to any particular modulation format or air-interface protocol. They are compatible with all current air-interface modulation schemes.
Adaptive smart antenna technology uses an adaptive-array approach and is realized as a combination of antennas (antenna arrays), analog RF and digital electronics, and estimation and detection algorithms. Resource allocation algorithms are used to make efficient use of system resources. A block diagram of a typical intelligent antenna system configuration is shown in Figure 1 on page 22.
With this basic configuration, capacity and coverage can be addressed with a common architecture. Optimal-processing, multiple-antenna outputs at a base station improve signal quality by strengthening the desired signal and by reducing interference (i.e., increased signal-to-interference-plus-noise ratio [SINR]). Although the details of algorithms used in a particular implementation depend on factors such as the temporal modulation format and the complexity of the RF environment, the objective of maximizing capacity and quality remains the same.
Shown in Figure 2 at the right are field test results for a suburban environment with an eight-element smart antenna DCS-1800 system developed in cooperation with Alcatel. The cumulative histograms collected during 25 minutes of driving at ranges from 5km to 15km from the base station show the improvement obtained by using a smart antenna system compared to a single antenna system, a 2-element switched diversity system (antenna separation about 4l) and a switched-beam system with eight beams covering a 120ø sector. These results indicate the potential uplink improvement that intelligent antenna systems provide compared to conventional single antenna and switched-diversity systems, as well as compared to proposed switched-beam systems_even those with extremely narrow beamwidths (nominally, 15ø in this case). The improvement compared to switched-beam antennas is in accordance with what would be expected, given the particular switched-beam characteristics that were chosen. The improvement over a single antenna system would be expected to be 9dB, and tests indicate that to be the case. Also as expected in such clean RF environments (where the fields remain highly correlated over large distances), switched-diversity performance is similar to that of a single-antenna system. Note that the 9dB improvement in uplink signal quality considerably increased the range at which the mobile unit’s signal could be demodulated successfully (roughly by a factor of two in these tests).
In Figure 3 on page 24, the potential ability of adaptive smart antenna technology to handle multiple co-channel signals is manifest. Shown are bit-error-rate (BER) measurements (using DCS-1800 signals) made for each of the aforementioned systems in the presence of an interfering signal of varying strength separated about 15ø in angular position from the desired signal. The noted improvement in SINR not only means signals can be received from greater distances (increased uplink range), but more than one can be received simultaneously (increased uplink capacity). Actually, interference in mobile systems is often the consequence of another customer attempting to use the system in another cell (spatial location).
In the downlink direction, multiple low-power transmitters selectively transmit information to one or more users on the same channel at the same time, reducing the amount of transmitted power required (interference to other users in other cells) while increasing capacity and range. Figure 4 on page 26 indicates the ability to transmit signals selectively on a common communication channel to different users in an 800MHz smart antenna system. Shown are cumulative histograms from data collected during a 10-minute drive test in a suburban environment, indicating the amount of signal vs. interference and noise received at one of several mobile units being communicated with simultaneously on a single channel during the test. Similar results were obtained for the other mobiles. The results indicate the potential of smart antenna systems to establish multiple links simultaneously and thereby increase capacity at a single cell site.
To quantify the system-level benefits of intelligent antenna technology, Table 1 above provides numerical examples of the improvement that could be expected by deploying a 10-element array and by assuming R3.5 range-dependent attenuation (or path loss exponent of 3.5). Note that for SINR improvements in excess of the stated signal-to-noise ratio (SNR) improvement, a requisite amount of interference must be present. Also, the reduction in base station emissions relates to traffic channels and does not account for broadcast-channel requirements associated with many mobile system protocols.
There is a growing need for improvements that increase coverage, capacity and quality in many wireless communication systems. Optimal exploitation of the spatial dimension through smart antenna technology has the potential to meet these needs in addition to providing operators the ability to offer new value-added products and services to their customers. Value-added services, obtainable with adaptive smart antenna technology, include location-based services such as taxi pickup, roadside services and fleet management. Additionally, E-9-1-1 emergency services and billing by location can be provided.
References 1. “Second Workshop on Smart Antennas in Wireless Mobile Communications,” Stanford University, Stanford, CA, July 1995.
2. “Third Workshop on Smart Antennas in Wireless Mobile Communications,” Stanford University, Stanford, CA, July 1996.