10-10-2014, 10:39 AM
BLAST
[attachment=68956]
ABSTRACT
BLAST is a wireless communications technique which uses multi-element antennas at both transmitter and receiver to permit transmission rates far in excess of those possible using conventional approaches.
In wireless systems, radio waves do not propagate simply from transmit antenna to receive antenna, but bounce and scatter randomly off objects in the environment. This scattering known as multipath, as it results in multiple copies (“images”) of the transmitted sign arriving at the receiver via different scattered paths. In conventional wireless system multipath represents a significant impediment to accurate transmission, because the image arrive at the receiver at slightly different times and can thus interfere destructively, canceling each other out. For this reason, multipath is traditionally viewed as a serious impairment. Using the BLAST approach however, it is possible to exploit multipath, that is, to use the scattering characteristics of the propagation environment to enhance, rather than degrade transmission accuracy by treating the multiplicity of scattering paths as separate parallel sub channels.
INTRODUCTION
The explosive growth of both the wireless industry and the Internet is creating a huge market opportunity for wireless data access. Limited internet access, at very low speeds, is already available as an enhancement to some existing cellular systems. However those systems were designed with purpose of providing voice services and at most short messaging, but not fast data transfer. Traditional wireless technologies are not very well suited to meet the demanding requirements of providing very high data rates with the ubiquity, mobility and portability characteristics of cellular systems. Increased use of antenna arrays appears to be the only means of enabling the type of data rates and capacities needed for wireless internet and multimedia services. While the deployment of base station arrays is becoming universal it is really the simultaneous deployment of base station and terminal arrays that can unleash unprecedented levels of performance by opening up multiple spatial signaling dimensions .Theoretically, user data rates as high as 2 Mb/sec will be supported in certain environments, although recent studies have shown that approaching those might only be feasible under extremely favorable conditions-in the vicinity of the base station and with no other users competing for band width. Some fundamental barriers related to the nature of radio channel as well as to the limited band width availability at the frequencies of interest stand in the way of high data rates and low cost associated with wide access.
FUNDAMENTAL LIMITATIONS IN WIRELESS DATA ACESS
Ever since the dawn of information age, capacity has been the principal metric used to asses the value of a communication system. Since the existing cellular system were devised almost exclusively for telephony, user data rates low .Infact the user data were reduced to the minimum level and traded for additional users. The value of a system is no longer defined only by how many users it can support, but also by its ability to provide high peak rates to individual users. Thus in the age of wireless data, user data rates surges as an important metric.
Trying to increase the data rates by simply transmitting more; Power is extremely costly. Furthermore it is futile in the contest of wherein an increase in everybody’s transmit power scales up both the desired signals as well as their mutual interference yielding no net benefit.
Increasing signal bandwidth along with the power is a more effective way of augmenting the data rate. However radio spectrum is a scarce and very expensive resource.Moreover increasing the signal bandwidth beyond the coherent bandwidth of the wireless channel results in frequency selectively. Although well-established technique such as equalization and OFDM can address this issue, their complexity grows with the signal bandwidth. Spectral efficiency defined as the capacity per unit bandwidth has become another key metric by which wireless systems are measured. In the contest of FDMA and TDMA, the evolutionary path has led to advanced forms of dynamic channel assessment that enable adaptive and more aggressive frequency reuse.In the context of multi-user detection and interference cancellation techniques.
BLAST’S SIGNAL DETECTION
At the receiver, an array of antennas is again used to pick up the multiple transmitted sub streams and their scattered images. Each receiver antenna sees the entire transmitted sub streams super imposed, not separately. However, if the multipath scattering is sufficient is sufficient, then the multiple sub streams are located at different points in space .Using sophisticated signal processing, these slight difference in scattering allow the sub streams to be identified and recovered. In effect the unavoidable multipath is exploited to provide a useful spatial parallelism that is used to greatly improve data transmission rates. Thus when using the BLAST technique, the more multipath, the better, just the opposite of the conventional systems.
The blast signal processing algorithms used at the receiver are the heart of the technique. At the bank of receiving antennas, high speed signal processors look at the signals from all the receiver antennas simultaneously, first extracting the strongest signal have been removed as a source of interference. Again the ability to separate the sub streams depends on the slight differences in the way the different sub streams propagate through the environment.
Let us assume a signal transmitted vector symbol with symbol-synchronous receiver sampling and ideal timing. If a= (a1, a2, a3,…. am) T is the vector transmitted symbols, then the receiver N vector is r1=Ha+v, where H is the matrix channel transfer function and V is a noise vector.
Signal detection can be done using adaptive, antenna array techniques, sometimes called linear combinational nulling. Each sub stream is sequentially understood as the desired signal. This implies that the other sub stream will be understood as interference. One nulls out this interference by weighting the interfering signals they go to zero (known as zero forcing).
While these linear nullings work, on linear approaches can be used in conjunction with them for overall result. Symbol cancellation is one such technique. Using interference from already detected components of interfering signals are subtracted to form the received signal vector. The end result is a modified receiver vector with few interferes present in the matrix. Bell labs actually tried both approaches. The result showed that adding the nonlinear to the linear yielded the best performance and dealing with the strongest channel, first (thus removing it as and interference) give the best overall SNR. If all components of ‘a’ are assumed to be the part of the same constellation, it would be expected that the component with the smallest SNR would dominate the overall error performance. The strongest channel then becomes the place to start symbol cancellation. This technique has been called the “best-first” approach and has become the de-facto way to do signal detection from an RF stream. But what the Bell labs guys found is that if you evaluate the SNR function at each stage of the detection process, rather than just at the beginning, you come up with a different ordering that is also (minmax) optimal.
As its core V-BLAST is an iterative cancellation method that depends on computing a matrix inverse to solve the zero forcing function. The algorithm works by detecting the strongest data stream from the received signal and repeating the process for the remaining data streams. While the algorithm complexity is linear with the number of transmitting antennas, it suffers performance degradation through the cancellation process. If cancellation is not perfect, it can inject more noise in to the system and degrade detection.
The essential difference between D-BLAST and V-BLAST lies in the vector encoding process. In D-BLAST, redundancy between the sub streams is introduced through the use of specialized inter-sub stream block coding. In D-BLAST code blocks are organized along diagonals in space-time. It is this coding that leads to D-BLAST’s higher spectral efficiencies for a given number of transmitters and receivers. In V-BLAST, however, the vector encoding process is simply a demultiplex operation followed by independent bit-to-symbol mapping of each sub stream. No inter-sub stream coding, or coding of any kind, is required, though conventional coding of the individual sub streams may certainly be applied.
ADVANTAGES
Since the entire sub streams are transmitted in the same frequency band, spectrum is used efficiently. Spectrally efficiency of 30-40 bps/Hz is achieved at SNR of 24 db. This is possible due to use of multiple antennas at the transmitter and receiver at SNR of 24 db. To achieve 40bps/Hz a conventional single antenna system would require a constellation with 10^12 points. Furthermore a constellation with such density of points would require in excess of 100db operating at any reasonable error rate.
A critical feature of BLAST is that the total radiated power is held constant irrespective of the number of transmitting antennas. Hence there is no increase in the amount interference caused to users.
Figure 5 displays cumulative distributions of system capacity (in megabits per second per sector) over all locations with transmit arrays only as well as with transmit and receive arrays. These curves can also be interpreted as user peaks rates, that is user data rates (in megabits per second) when the entire capacity of every sector is allocated to an individual user. With transmit arrays only; the benefit appears significant only in the lower tail of the distribution, corresponding to users in the most detrimental location. The improvements in average and peak systems capacities are negligible. Moreover, the gains saturate rapidly as additional transmit antennas are added. With frequency diversity taken into account, those gains would be reduced even further. The combined use of transmit and receive arrays, on the other hand , dramatically shifts the curves offering multifold improvements in data rate at all levels. Notice that, without receive arrays, the peak data rate that can be supported in 90 per-cent of the systems locations-with a single user per sector –is only on the order of 500kb/s with no transmit diversity and just over 1Mb/s there-with.
CONCLUSION
Under widely used theoretical assumption of independent Rayleigh scattering theoretical capacity of the BLAST architecture grows roughly, linearly with the number of antennas even when the total transmitted power is held constant. In the real world ofcourse scattering will be less favorable than the independent Raleigh’s assumption ant it remains to be seen how much capacity is actually available in various propagation environments. Nevertheless, even in relatively poor scattering environment, BLAST should be able to provide significantly higher capacities than conventional architectures
[attachment=68956]
ABSTRACT
BLAST is a wireless communications technique which uses multi-element antennas at both transmitter and receiver to permit transmission rates far in excess of those possible using conventional approaches.
In wireless systems, radio waves do not propagate simply from transmit antenna to receive antenna, but bounce and scatter randomly off objects in the environment. This scattering known as multipath, as it results in multiple copies (“images”) of the transmitted sign arriving at the receiver via different scattered paths. In conventional wireless system multipath represents a significant impediment to accurate transmission, because the image arrive at the receiver at slightly different times and can thus interfere destructively, canceling each other out. For this reason, multipath is traditionally viewed as a serious impairment. Using the BLAST approach however, it is possible to exploit multipath, that is, to use the scattering characteristics of the propagation environment to enhance, rather than degrade transmission accuracy by treating the multiplicity of scattering paths as separate parallel sub channels.
INTRODUCTION
The explosive growth of both the wireless industry and the Internet is creating a huge market opportunity for wireless data access. Limited internet access, at very low speeds, is already available as an enhancement to some existing cellular systems. However those systems were designed with purpose of providing voice services and at most short messaging, but not fast data transfer. Traditional wireless technologies are not very well suited to meet the demanding requirements of providing very high data rates with the ubiquity, mobility and portability characteristics of cellular systems. Increased use of antenna arrays appears to be the only means of enabling the type of data rates and capacities needed for wireless internet and multimedia services. While the deployment of base station arrays is becoming universal it is really the simultaneous deployment of base station and terminal arrays that can unleash unprecedented levels of performance by opening up multiple spatial signaling dimensions .Theoretically, user data rates as high as 2 Mb/sec will be supported in certain environments, although recent studies have shown that approaching those might only be feasible under extremely favorable conditions-in the vicinity of the base station and with no other users competing for band width. Some fundamental barriers related to the nature of radio channel as well as to the limited band width availability at the frequencies of interest stand in the way of high data rates and low cost associated with wide access.
FUNDAMENTAL LIMITATIONS IN WIRELESS DATA ACESS
Ever since the dawn of information age, capacity has been the principal metric used to asses the value of a communication system. Since the existing cellular system were devised almost exclusively for telephony, user data rates low .Infact the user data were reduced to the minimum level and traded for additional users. The value of a system is no longer defined only by how many users it can support, but also by its ability to provide high peak rates to individual users. Thus in the age of wireless data, user data rates surges as an important metric.
Trying to increase the data rates by simply transmitting more; Power is extremely costly. Furthermore it is futile in the contest of wherein an increase in everybody’s transmit power scales up both the desired signals as well as their mutual interference yielding no net benefit.
Increasing signal bandwidth along with the power is a more effective way of augmenting the data rate. However radio spectrum is a scarce and very expensive resource.Moreover increasing the signal bandwidth beyond the coherent bandwidth of the wireless channel results in frequency selectively. Although well-established technique such as equalization and OFDM can address this issue, their complexity grows with the signal bandwidth. Spectral efficiency defined as the capacity per unit bandwidth has become another key metric by which wireless systems are measured. In the contest of FDMA and TDMA, the evolutionary path has led to advanced forms of dynamic channel assessment that enable adaptive and more aggressive frequency reuse.In the context of multi-user detection and interference cancellation techniques.
BLAST’S SIGNAL DETECTION
At the receiver, an array of antennas is again used to pick up the multiple transmitted sub streams and their scattered images. Each receiver antenna sees the entire transmitted sub streams super imposed, not separately. However, if the multipath scattering is sufficient is sufficient, then the multiple sub streams are located at different points in space .Using sophisticated signal processing, these slight difference in scattering allow the sub streams to be identified and recovered. In effect the unavoidable multipath is exploited to provide a useful spatial parallelism that is used to greatly improve data transmission rates. Thus when using the BLAST technique, the more multipath, the better, just the opposite of the conventional systems.
The blast signal processing algorithms used at the receiver are the heart of the technique. At the bank of receiving antennas, high speed signal processors look at the signals from all the receiver antennas simultaneously, first extracting the strongest signal have been removed as a source of interference. Again the ability to separate the sub streams depends on the slight differences in the way the different sub streams propagate through the environment.
Let us assume a signal transmitted vector symbol with symbol-synchronous receiver sampling and ideal timing. If a= (a1, a2, a3,…. am) T is the vector transmitted symbols, then the receiver N vector is r1=Ha+v, where H is the matrix channel transfer function and V is a noise vector.
Signal detection can be done using adaptive, antenna array techniques, sometimes called linear combinational nulling. Each sub stream is sequentially understood as the desired signal. This implies that the other sub stream will be understood as interference. One nulls out this interference by weighting the interfering signals they go to zero (known as zero forcing).
While these linear nullings work, on linear approaches can be used in conjunction with them for overall result. Symbol cancellation is one such technique. Using interference from already detected components of interfering signals are subtracted to form the received signal vector. The end result is a modified receiver vector with few interferes present in the matrix. Bell labs actually tried both approaches. The result showed that adding the nonlinear to the linear yielded the best performance and dealing with the strongest channel, first (thus removing it as and interference) give the best overall SNR. If all components of ‘a’ are assumed to be the part of the same constellation, it would be expected that the component with the smallest SNR would dominate the overall error performance. The strongest channel then becomes the place to start symbol cancellation. This technique has been called the “best-first” approach and has become the de-facto way to do signal detection from an RF stream. But what the Bell labs guys found is that if you evaluate the SNR function at each stage of the detection process, rather than just at the beginning, you come up with a different ordering that is also (minmax) optimal.
As its core V-BLAST is an iterative cancellation method that depends on computing a matrix inverse to solve the zero forcing function. The algorithm works by detecting the strongest data stream from the received signal and repeating the process for the remaining data streams. While the algorithm complexity is linear with the number of transmitting antennas, it suffers performance degradation through the cancellation process. If cancellation is not perfect, it can inject more noise in to the system and degrade detection.
The essential difference between D-BLAST and V-BLAST lies in the vector encoding process. In D-BLAST, redundancy between the sub streams is introduced through the use of specialized inter-sub stream block coding. In D-BLAST code blocks are organized along diagonals in space-time. It is this coding that leads to D-BLAST’s higher spectral efficiencies for a given number of transmitters and receivers. In V-BLAST, however, the vector encoding process is simply a demultiplex operation followed by independent bit-to-symbol mapping of each sub stream. No inter-sub stream coding, or coding of any kind, is required, though conventional coding of the individual sub streams may certainly be applied.
ADVANTAGES
Since the entire sub streams are transmitted in the same frequency band, spectrum is used efficiently. Spectrally efficiency of 30-40 bps/Hz is achieved at SNR of 24 db. This is possible due to use of multiple antennas at the transmitter and receiver at SNR of 24 db. To achieve 40bps/Hz a conventional single antenna system would require a constellation with 10^12 points. Furthermore a constellation with such density of points would require in excess of 100db operating at any reasonable error rate.
A critical feature of BLAST is that the total radiated power is held constant irrespective of the number of transmitting antennas. Hence there is no increase in the amount interference caused to users.
Figure 5 displays cumulative distributions of system capacity (in megabits per second per sector) over all locations with transmit arrays only as well as with transmit and receive arrays. These curves can also be interpreted as user peaks rates, that is user data rates (in megabits per second) when the entire capacity of every sector is allocated to an individual user. With transmit arrays only; the benefit appears significant only in the lower tail of the distribution, corresponding to users in the most detrimental location. The improvements in average and peak systems capacities are negligible. Moreover, the gains saturate rapidly as additional transmit antennas are added. With frequency diversity taken into account, those gains would be reduced even further. The combined use of transmit and receive arrays, on the other hand , dramatically shifts the curves offering multifold improvements in data rate at all levels. Notice that, without receive arrays, the peak data rate that can be supported in 90 per-cent of the systems locations-with a single user per sector –is only on the order of 500kb/s with no transmit diversity and just over 1Mb/s there-with.
CONCLUSION
Under widely used theoretical assumption of independent Rayleigh scattering theoretical capacity of the BLAST architecture grows roughly, linearly with the number of antennas even when the total transmitted power is held constant. In the real world ofcourse scattering will be less favorable than the independent Raleigh’s assumption ant it remains to be seen how much capacity is actually available in various propagation environments. Nevertheless, even in relatively poor scattering environment, BLAST should be able to provide significantly higher capacities than conventional architectures