Practical space-time radio method for CDMA communication...

Telecommunications – Transmitter and receiver at same station – Radiotelephone equipment detail

Reexamination Certificate

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Details

C455S550100

Reexamination Certificate

active

06347234

ABSTRACT:

FIELD OF INVENTION
The present invention relates to wireless communication systems. More specifically, the invention relates to methods for enhancement of wireless communication performance by exploiting the spatial domain, and practical systems for implementing such methods.
BACKGROUND
Due to the increasing demand for wireless communication, it has become necessary to develop techniques for more efficiently using the allocated frequency bands, i.e., increasing the capacity to communicate information within a limited available bandwidth. In conventional low capacity wireless communication systems, information is transmitted from a base station to subscribers by broadcasting omnidirectional signals on one of several predetermined frequency channels. Similarly, the subscribers transmit information back to the base station by broadcasting similar signals on one of the frequency channels. In this system, multiple users independently access the system through the division of the frequency band into distinct subband frequency channels. This technique is known as frequency division multiple access (FDMA).
A standard technique used by commercial wireless phone systems to increase capacity is to divide the service region into spatial cells. Instead of using just one base station to serve all users in the region, a collection of base stations are used to independently service separate spatial cells. In such a cellular system, multiple users can reuse the same frequency channel without interfering with each other, provided they access the system from different spatial cells. The cellular concept, therefore, is a simple type of spatial division multiple access (SDMA).
In the case of digital communication, additional techniques can be used to increase capacity. A few well known examples are time division multiple access (TDMA) and code division multiple access (CDMA). TDMA allows several users to share a single frequency channel by assigning their data to distinct time slots. CDMA is normally a spread-spectrum technique that does not limit individual signals to narrow frequency channels but spreads them throughout the frequency spectrum of the entire band. Signals sharing the band are distinguished by assigning them different orthogonal digital code sequences. CDMA has been considered the most promising method among the various air-interfaces in the industry, as shown by theoretical analysis and recent increase in use.
Despite the promise of CDMA, practical issues such as power control speed and inter-base station interference considerably limited system effectiveness in its initial phase of implementation. CDMA based system capacity depends very much on the ability to provide for very accurate power control; but in a mobile environment, the signal may fluctuate too fast for the system to manage effective control. In addition, mobile wireless environments are often characterized by unstable signal propagation, severe signal attenuation between the communicating entities and co-channel interference by other radio sources. Moreover, many urban environments contain a significant number of reflectors (such as buildings), causing a signal to follow multiple paths from the transmitter to the receiver. Because the separate parts of such a multipath signal can arrive with different phases that destructively interfere, multipath can result in unpredictable signal fading. In addition, in order to provide service to shadowed areas, radiated power is increased, thereby increasing interference between base stations and significantly degrading system performance.
Recently, considerable attention has focused on ways to increase wireless system performance by further exploiting the spatial domain. It is well recognized that SDMA techniques could, in principle, significantly improve the CDMA based network performance. In practice, however, such significant improvements have yet to be realized. Currently proposed approaches are either simple but not very effective or effective but too complex for practical implementation.
One well-known SDMA technique is to provide the base station with a set of independently controlled directional antennas, thereby dividing the cell into separate fixed sectors, each controlled by a separate antenna. As a result, the frequency reuse in the system can be increased and/or cochannel interference can be reduced. A similar but more complex technique can be implemented with a coherently controlled antenna array instead of independently controlled directional antennas. Using a signal processor to control the relative phases of the signals applied to the antenna array elements, predetermined beams can be formed in the directions of the separate sectors. Similar signal processing can be used to selectively receive signals only from within the distinct sectors. These simple sectoring techniques, however, only provide a relatively small increase in capacity.
U.S. Pat. No. 5,563,610 discloses a method for mitigating signal fading due to multipath in a CDMA system. By introducing intentional delays into received signals, non-correlated fading signal components can be better differentiated by the RAKE receiver. Although this diversity method can reduce the effects of fading, it does not take advantage of the spatial domain and does not directly increase system capacity. Moreover, this approach, which combines angular and time diversity using a fixed beam configuration, is not effective since either the beam outputs are significantly different in level or they are similar in level but highly correlated. If two signal parts are arriving from a similar direction, they are passing through one beam and thus are not spatially distinguishable. If the signal parts are arriving between beams, on the other hand, the levels are similar but then they are highly correlated.
More sophisticated SDMA techniques have been proposed that theoretically could dramatically increase system capacity. For example, U.S. Pat. Nos. 5,471,647 and 5,634,199, both to Gerlach et al., and U.S. Pat. No. 5,592,490 to Barratt et al. disclose wireless communication systems that increase performance by exploiting the spatial domain. In the downlink, the base station determines the spatial channel of each subscriber and uses this channel information to adaptively control its antenna array to form customized narrow beams. These beams transmit an information signal over multiple paths so that the signal arrives to the subscriber with maximum strength. The beams can also be selected to direct nulls to other subscribers so that cochannel interference is reduced. In the uplink, the base station uses the channel information to spatially filter the received signals so that the uplink signal is received with maximum sensitivity and distinguished from the signals transmitted by other subscribers. Through selective power delivery by intelligent directional beams, the interference between base stations and the carrier-to-interference ratio at the base station receivers can be reduced.
The biggest issue in adaptive beamforming is how to quickly estimate the wireless air channel to allow for effective beam allocation. In the uplink, there are known signal processing techniques for estimating the spatial channel from the signals received at the base station antenna array. These techniques conventionally involve an inversion or singular value decomposition of a signal covariance matrix. The computational complexity of this calculation, however, is so high that it is presently not practical to implement. These highly complex approaches capitalize on the theory of array signal processing. These approaches estimate the uplink channel (e.g. the angles and times of arrival of the multipath signal parts) to create a space-time matched filter to allow for maximum signal delivery. The method involves computation of a signal covariance matrix and derivation of its eigenvectors to determine the array coefficients. The basic equation of array signal processing is:
X=AS+N,
where X is a matrix of antenna array signal snapshots (each column

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