- Perspectives in Propagation
- The Case for Space
- Trends in Wireless Communications
- About This Book
This chapter is from the book
This chapter is from the book
This chapter is from the book
1.3 Trends in Wireless Communications
The theory that engineers use to measure and model wireless communications has changed very little over the last 30 years. The main reason for this stagnation of development may be summed up as follows: The current theory still works for wireless systems that have been deployed to date. Do not expect this to hold much longer. There are six trends in wireless communications that emphasize the need for improved and expanded channel modeling theory.
1.3.1 Higher and Higher Data Rates
The capacity for data transmission of current wireless systems is still tiny when compared to wired forms of communications. But wireless data rates continue to increase. To understand the push for higher and higher data rates, it is useful to consider an analogy involving the trends of memory size and processor speed in the personal computer market. In the early 1980s, a typical personal computer had about 64 kilobytes of RAM and operated with a processor that clocked at speeds less than 1 MHz. In 2000, the typical personal computer had a processor that operated at a clock frequency close to 1 GHz and required as much as 100 MB of RAM. In short, as soon as computer hardware is enhanced, new commercial software applications are developed that exploit the newfound capacity for storing and manipulating data.
The computer hardware illustration provides a valuable lesson for the wireless industry. There is a basic rule that applies to all information technology: Technology that increases the capacity to store or manipulate data is eventually (and sometimes rapidly) followed by new applications that exhaust the resources. For wireless, this means that the current technology will continue to gravitate towards higher transmitted data rates [Rap02b].
Of course, higher data rates imply wireless systems that operate with wider bandwidths. Future wireless systems will operate with bandwidths that greatly exceed conventional channel models. New systems will require new channel models and measurements.
1.3.2 Ubiquity of Wireless Devices
Wireless personal communications has permeated nearly every environment on earth. It is now possible to use a wireless handset in a city, in a car, in the home, in an oLce building, on a boat - the list goes on. Future applications will involve wireless sensors and impersonal communications between engines, machinery, and appliances.
The wireless channel is heavily dependent on the environment in which it operates. Since future wireless applications will operate in nearly every imaginable environment, there will be an incredibly diverse variety of channels that require characterization. In fact, many of these new environments will defy characterization by the older paradigms of wireless channel modeling.
1.3.3 Smart Antennas
Adaptive arrays and other types of smart antenna techniques are emerging technologies for improving the wireless link and mitigating interference in a multiple access system [God97], [Win98]. Many multiuser communication systems such as cellular radio networks had, until the end of the 20th century, operated below their designed capacity. As the market for these systems has grown and matured, the network traLc has grown as well. Smart antenna technology is seen as a cheap and eAective solution for mitigating the problem of network congestion.
A directional antenna at a receiver or transmitter drastically changes the channel characteristics. Channel models that once applied to omnidirectional antennas must be modified and improved to account for the new space–time distortion of the channel by the directional antenna.
1.3.4 Faster, Smaller, Cheaper Hardware
Over the years, basic research in wireless communications has produced a plethora of modulation, multiple-access, and signal-processing innovations that combat the distortions introduced by a wireless channel. Only a small subset of these innovations are used in practice, since many algorithms and techniques do not have a feasible realization in hardware.
Radio frequency and digital signal-processing technology continues to develop, however. The computational power of baseband chipsets is increasing. The radio-frequency integrated circuits are operating at higher power levels and at higher frequencies. Above all, these transmitter and receiver components are becoming cheaper and cheaper to fabricate. As a result, many algorithms and techniques that are not feasible to implement today will become feasible tomorrow.
The added capabilities of future radio receivers, therefore, will be able to combat the detrimental eAects of the multipath channel in new and innovative ways. With added functionality, receivers of the future need more than just an ad hoc approximation about the radio channel. Future receiver designs will require models that mimic the detailed dispersion, time-varying, and space-varying characteristics of a realistic wireless channel.
1.3.5 Frequency Congestion
Bandwidth is a finite resource. As wireless systems with wider and wider bandwidths continue to deploy, frequency congestion becomes a problem. One solution is to move outside of common frequency bands and into higher, uncrowded frequency in the upper microwave and mm-wave bands. Propagation at these higher frequencies presents an entirely diAerent set of problems. Channel models developed around the 1 GHz microwave bands are inadequate to characterize wireless systems where both the carrier frequency and signal bandwidth are one or two orders of magnitude greater.
1.3.6 Multiple-Input, Multiple-Output Systems
Perhaps one of the most interesting trends in wireless communications is the proposed use of multiple-input, multiple-output (MIMO) systems. A MIMO system uses multiple transmitter antennas and multiple receiver antennas to break a multipath channel into several individual spatial channels. Such a system employs space–time coding to increase the link capacity [Fos96].
New MIMO systems represent a huge change in how wireless communications systems are designed. This change reflects how we view multipath in a wireless system: The Old Perspective: The ultimate goal of wireless communications is to combat the distortion caused by multipath in order to approach the theoretical limit of capacity for a band-limited channel.
The New Perspective: Since multipath propagation actually represents multiple channels between a transmitter and receiver, the ultimate goal of wireless communications is to use multipath to provide higher total capacity than the theoretical limit for a conventional band-limited channel.
This philosophical reversal implies that many of the engineering design rules of thumb that were based on pessimistic, worst-case scenario channel models have now become unrealistically optimistic. Design of such systems will require new space–time channel models.