Its so easy to put up posts wen u've researched on something and made clear studies on every word taht u have put. Making a thesis, putting in points, editing, cut-copy-paste, all these become all so common. Ive done my project well, put down every point only after serious consideration and worked hard to get the result. But is this all that I have learnt? That MIMO improves capacity. That ML is the most optimum detector. That VBLAST is an efficient architecture.
NO !! There are so many things I learnt on this one semester wich i havent for the last 4 yrs. Ive known that I had wasted 4 yrs of my life by being in one of the best fields in the professional degree and stil having not known it. I hav learnt that in no other field can we see so much of advancements in technology every day, every second. I hav seen the wonders that electronics can bring to the world. I hav felt the change a degree can make to my life. I hav understood all concepts I forgot to in my 4 yrs within semester. I hav understood why some professors are so irritated with us. I hav learnt that even the most boring lecture will hav some point that will be useful for, tat I had never known. I hav learnt the basics of finance. I know why inflation occurs. I can easily convert dollars to rupees. I know that 9 is a very powerful number and it spells doom to have ur life number and death number as the same. I found that my husband is gonna suffer wid me. I have learnt that I shud never look down upon anyone by the job they do. You never no...They may act be millionaires working to kill time. I hav seen that its never too late to learn, all u need is interest. The entire world is waiting to help u out. All you need to do is stretch out that hand.
Now wen I come out of my dept, wen I leave coll I will never complain for having taken this stream cos I no Im way ahead of so many cos of the field i had chosen to do. Im proud to be an Engineer, Proud to be ECEian, Proud to be an SSNite and esp esp proud to have been under my batch.
Thursday, March 27, 2008
Wednesday, March 26, 2008
My conclusions at the end of this project
The primary focus that I had undertaken in my project was to assay the MIMO system over AWGN and Rayleigh to mitigate MAI. The channel model was built on the classical understanding of fading, Doppler spread and delay spread. The transmitted signal is assumed to be corrupted by multipath and MAI, in accession to AWGN at the front end of the receiver. As anticipated, the system is interference limited. It is discerned that the Multi User Detection employing linear and non linear detection techniques at the receiver can exterminate MAI and intra-cell interferences. Investigations of the simulation results reveal that Multi User Detection can ameliorate the capacity of the MIMO channels for coded signals. It is also seen that each technique is preferred for particular environments based on the complexity of the technique. It was seen that ML was the optimum method but MAP with ZF provided the same performance as ML. Also it was seen that though ML had low complexity than MAP for less number of antennas the complexity increased linearly with increase in antennas.
It was found out that in case error control coding techniques like Low Density Parity Check (LDPC) and Turbo Codes had been employed in this work the robustness of the MIMO communication system would have been improved. But due to constraint on the time we were not able to do further research on the same. Anyhow since this is an emerging field it can be envisioned that as future mobile communication especially 4G will be employing beamforming technique, this can also be considered as additional work.
It was found out that in case error control coding techniques like Low Density Parity Check (LDPC) and Turbo Codes had been employed in this work the robustness of the MIMO communication system would have been improved. But due to constraint on the time we were not able to do further research on the same. Anyhow since this is an emerging field it can be envisioned that as future mobile communication especially 4G will be employing beamforming technique, this can also be considered as additional work.
Tuesday, March 25, 2008
My disclosure policy
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To get your own policy, go to http://www.disclosurepolicy.org
The compensation received will never influence the content, topics or posts made in this blog. All advertising is in the form of advertisements generated by a third party ad network. Those advertisements will be identified as paid advertisements.
The owner(s) of this blog is compensated to provide opinion on products, services, websites and various other topics. Even though the owner(s) of this blog receives compensation for our posts or advertisements, we always give our honest opinions, findings, beliefs, or experiences on those topics or products. The views and opinions expressed on this blog are purely the bloggers’ own. Any product claim, statistic, quote or other representation about a product or service should be verified with the manufacturer, provider or party in question.
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Monday, March 24, 2008
Now for the Various Techniques...
**ZF-This is an equalization technique in which the received signal is multiplied by a weighted vector such that the Inter Symbol Interference (ISI) is forced to zero. This value is chosen from the Channel Matrix (H) which provides the channel state information. The disadvantage in Zf is that since it amplifies the noise components along with he signal it is not much preferred.
**MMSE-The MMSE receiver suppresses both the interference and noise components, whereas the ZF receiver removes only the interference components. This implies that the mean square error between the transmitted symbols and the estimate of the receiver is minimized. Hence, MMSE is superior to ZF in the presence of noise.
**MAP-This algorithm is used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is optimum as it minimizes the probability of error. MAP instead of selecting the next symbol to be detected according to the rule, here the set of all potential symbol decisions are ranked with respect to their a posteriori probabilities of being correct. The index permutation produced by MAP depends on both H (Channel Matrix) and r(received signal) , unlike ZF where permutation depends only on H . So the major complexity in MAP is that the weighting vector must be computed in real time since it also depends on r.
**ML-It brings out the optimal performance. It is a special case of MAP detection when all possible inputs are equally likely. The major advantage of ML over MAP is that the likelihood is easily computed for each possible symbol knowing the statistics of noise generator and not statistics of data symbol. ML and MAP are different detection techniques, but yield the same result when the priori probabilities are equal. However If priori probabilities are different, MAP yields lower probability of error.
**N/C-Nulling and cancelling (NC) uses a serial decision-feedback approach to detect each layer separately. When a layer has been detected, an estimate of the corresponding contribution to the received vector r is subtracted from; the result is then used to detect the next layer and so on. N/C progressively clears r from the interference corresponding to the layers already detected. To detect a specific layer, the layers that have not been detected yet are “nulled out” (equalized) according to the ZF or MMSE approach. Error propagation can be a problem because incorrect data decisions actually increase the interference when detecting subsequent layers. Thus, the order in which the layers are detected strongly influences the performance of NC.
**MMSE-The MMSE receiver suppresses both the interference and noise components, whereas the ZF receiver removes only the interference components. This implies that the mean square error between the transmitted symbols and the estimate of the receiver is minimized. Hence, MMSE is superior to ZF in the presence of noise.
**MAP-This algorithm is used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is optimum as it minimizes the probability of error. MAP instead of selecting the next symbol to be detected according to the rule, here the set of all potential symbol decisions are ranked with respect to their a posteriori probabilities of being correct. The index permutation produced by MAP depends on both H (Channel Matrix) and r(received signal) , unlike ZF where permutation depends only on H . So the major complexity in MAP is that the weighting vector must be computed in real time since it also depends on r.
**ML-It brings out the optimal performance. It is a special case of MAP detection when all possible inputs are equally likely. The major advantage of ML over MAP is that the likelihood is easily computed for each possible symbol knowing the statistics of noise generator and not statistics of data symbol. ML and MAP are different detection techniques, but yield the same result when the priori probabilities are equal. However If priori probabilities are different, MAP yields lower probability of error.
**N/C-Nulling and cancelling (NC) uses a serial decision-feedback approach to detect each layer separately. When a layer has been detected, an estimate of the corresponding contribution to the received vector r is subtracted from; the result is then used to detect the next layer and so on. N/C progressively clears r from the interference corresponding to the layers already detected. To detect a specific layer, the layers that have not been detected yet are “nulled out” (equalized) according to the ZF or MMSE approach. Error propagation can be a problem because incorrect data decisions actually increase the interference when detecting subsequent layers. Thus, the order in which the layers are detected strongly influences the performance of NC.
Multi User Detecion
Here I come to the main portion of my project...The evaluation for various detectors and finding the optimal one. First once more on MUD.
The use of multiple antennas at the transmitter and receiver results in Multiple Access Interference (MAI). Delay spread causes Inter-Symbol Interference (ISI). ISI can cause an irreducible error floor when the modulation symbol time is on the same order as the channel delay spread. Equalization defines any signal processing technique used at the receiver to alleviate the ISI problem caused by delay spread.Equalization techniques fall into two broad categories: linear and nonlinear. The linear techniques are generally the simplest to implement and to understand conceptually. However, they typically suffer from more noise enhancement than nonlinear equalizers, and are therefore not used in most wireless applications. We had considered Zero Forcing (ZF), Mean Square Error (MMSE) and Maximum a Posteriori (MAP) under linear equalizers and Nulling/Cancelaltion (N/C) and Maximum Likelihood (ML) under non-linear methods. Now to see them one by one.
The use of multiple antennas at the transmitter and receiver results in Multiple Access Interference (MAI). Delay spread causes Inter-Symbol Interference (ISI). ISI can cause an irreducible error floor when the modulation symbol time is on the same order as the channel delay spread. Equalization defines any signal processing technique used at the receiver to alleviate the ISI problem caused by delay spread.Equalization techniques fall into two broad categories: linear and nonlinear. The linear techniques are generally the simplest to implement and to understand conceptually. However, they typically suffer from more noise enhancement than nonlinear equalizers, and are therefore not used in most wireless applications. We had considered Zero Forcing (ZF), Mean Square Error (MMSE) and Maximum a Posteriori (MAP) under linear equalizers and Nulling/Cancelaltion (N/C) and Maximum Likelihood (ML) under non-linear methods. Now to see them one by one.
Sunday, March 23, 2008
Employing MIMO
The use of multiple antennas at the transmitter and receiver in wireless systems, popularly known as MIMO (multiple input multiple output) technology, has rapidly gained in popularity over the past decade due to its powerful performance enhancing capabilities. It offers a number of benefits that enables to meet the challenges posed by both the resource constraints and the impairments in wireless communication. In addition to the time and frequency dimension that are exploited in single-antenna system, multiple antennas exploit spatial dimension. Over the past few years, it has been shown that using multiple antennas can significantly increase the capacity and robustness of communication systems in fading environments. Capacity grows with the number of antennas used.
To achieve the capacities promised using MIMO scheme Bell Labs proposed an architecture known as Bell Labs Space Time (BLAST) architecture. To overcome the implementation complexities modified version known as Vertical Bell Labs Space Time or VBLAST was proposed.
In this architecture a single data stream is demultiplexed into M sub streams, and each sub stream is then encoded into symbols and fed to its respective transmitter. It is assumed that the same constellation is used for each sub stream and that the transmissions are organized into bursts of L symbols. The rich scattering environment that is considered is rayleigh fading channel characterized by weak LoS and strong scatterers. At the receiver side each antenna receives signals from all the transmitters and the various versions of the signal are combined, then estimated and decoded to get the symbol.
To achieve the capacities promised using MIMO scheme Bell Labs proposed an architecture known as Bell Labs Space Time (BLAST) architecture. To overcome the implementation complexities modified version known as Vertical Bell Labs Space Time or VBLAST was proposed.
In this architecture a single data stream is demultiplexed into M sub streams, and each sub stream is then encoded into symbols and fed to its respective transmitter. It is assumed that the same constellation is used for each sub stream and that the transmissions are organized into bursts of L symbols. The rich scattering environment that is considered is rayleigh fading channel characterized by weak LoS and strong scatterers. At the receiver side each antenna receives signals from all the transmitters and the various versions of the signal are combined, then estimated and decoded to get the symbol.
Space Time Block Codes
Well i had talked abt us using coded signals. That brings us to Space Time codes. These are used at the transmitter to exploit the spatial domain, which means while the time, frequency remains the same the code alone differs for the different systems. This is analogous to CDMA technology but the difference lies in that while CDMA employs single channel in this multiple channels are realized.So here i give a gist on Space Time Block codes.
STBC is an extension of transmit diversty. Here at one instant of time the data is sent via the separate antennas by coding them using orthogonal codes. STBC is a generalization of Alamouti's code discovered by Alamouti for transmission using two transmitting antennas. The scheme can be described as below:
The information bits are first modulated using an M-ary modulation scheme. The encoder then takes a block of two modulated symbols s1 and s2 in each encoding operation and gives it to the transmit antennas according to the code matrix,
S=[s1 -s2* ; s2 s1*]
The first column represents the first transmission period and the second column the second transmission period. The first row corresponds to the symbols transmitted from the first antenna and the second row corresponds to the symbols transmitted from the second antenna. This implies that we are transmitting both in space (across two antennas) and time (two transmission intervals). This is space-time coding. By extending this to more than 2 antennas the theory behind STBC was formulated.
At the receiver side these various versions are combined and estimated. Then this value is sent to the maximum likelihood detector that minimizes the decision metric and decodes the symbols s1 and s2.
STBC is an extension of transmit diversty. Here at one instant of time the data is sent via the separate antennas by coding them using orthogonal codes. STBC is a generalization of Alamouti's code discovered by Alamouti for transmission using two transmitting antennas. The scheme can be described as below:
The information bits are first modulated using an M-ary modulation scheme. The encoder then takes a block of two modulated symbols s1 and s2 in each encoding operation and gives it to the transmit antennas according to the code matrix,
S=[s1 -s2* ; s2 s1*]
The first column represents the first transmission period and the second column the second transmission period. The first row corresponds to the symbols transmitted from the first antenna and the second row corresponds to the symbols transmitted from the second antenna. This implies that we are transmitting both in space (across two antennas) and time (two transmission intervals). This is space-time coding. By extending this to more than 2 antennas the theory behind STBC was formulated.
At the receiver side these various versions are combined and estimated. Then this value is sent to the maximum likelihood detector that minimizes the decision metric and decodes the symbols s1 and s2.
Saturday, March 22, 2008
In simple terms...First MUD
I no the prev msg had lines that cud not be comprehended in one read. In fact it cant be comprehended after many reads also cos it has many terms. So here i provide an easier explanation for each term employed.
First what is Multi-User Detection (MUD)?
Any multi user communication system is inherently interference limited. With the increase in number of users, interference between the users known as Multiple Access Interference or MAI swells, severely hindering the system capacity. Therefore there exist a need for an efficient algorithm that will cancel, limit, avoid or reduce interference. In the case of Conventional receivers (eg. matched filter) the received signals from other users are treated as noise and are decoded independently. However, since signals from other users are also required for decoding at the base station, estimates of signals from other users can be used to estimate the interference and cancel it from the desired signal. This leads to the concept called Multi-User Detection (MUD).
First what is Multi-User Detection (MUD)?
Any multi user communication system is inherently interference limited. With the increase in number of users, interference between the users known as Multiple Access Interference or MAI swells, severely hindering the system capacity. Therefore there exist a need for an efficient algorithm that will cancel, limit, avoid or reduce interference. In the case of Conventional receivers (eg. matched filter) the received signals from other users are treated as noise and are decoded independently. However, since signals from other users are also required for decoding at the base station, estimates of signals from other users can be used to estimate the interference and cancel it from the desired signal. This leads to the concept called Multi-User Detection (MUD).
Friday, March 21, 2008
Performance Evaluation of Multi-Stage Receivers for coded signals in MIMO channels
The abstract can be given as below:
Wireless Communication is one of the most vibrant areas in the communication field today. The past decade has seen a surge of research activities in the area, especially in designing faster, more reliable and power efficient wireless communication system. As a novel technology, multi-antenna communication especially MIMO system has gained lot of interest and has been considered as a key technology for Broadband 3G communication. By exploiting the spatial diversity using multiple antennas one can improve reliability, increase throughput and reduce transmission power. The performance on the uplink degrades as the interference swells. The main objective of this thesis is to propound interference cancellation technique called Multi-User Detection (MUD) to mitigate the effects of Multiple Access Interference (MAI), which limits the capacity of the system. The performance of various Multi-User receivers for VBLAST and STBC are studied and analyzed. Also the performance comparison of sub-optimal detectors such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE), QR Factorization, Nulling and Cancellation Detector, Zero Forcing/Maximum A Posteriori (ZF/MAP) and optimal detectors like Maximum Likelihood (ML) are assayed through simulation. It is discerned that MUD provides remarkable amelioration in terms of mitigating MAI for coded signals on MIMO channels.
Wireless Communication is one of the most vibrant areas in the communication field today. The past decade has seen a surge of research activities in the area, especially in designing faster, more reliable and power efficient wireless communication system. As a novel technology, multi-antenna communication especially MIMO system has gained lot of interest and has been considered as a key technology for Broadband 3G communication. By exploiting the spatial diversity using multiple antennas one can improve reliability, increase throughput and reduce transmission power. The performance on the uplink degrades as the interference swells. The main objective of this thesis is to propound interference cancellation technique called Multi-User Detection (MUD) to mitigate the effects of Multiple Access Interference (MAI), which limits the capacity of the system. The performance of various Multi-User receivers for VBLAST and STBC are studied and analyzed. Also the performance comparison of sub-optimal detectors such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE), QR Factorization, Nulling and Cancellation Detector, Zero Forcing/Maximum A Posteriori (ZF/MAP) and optimal detectors like Maximum Likelihood (ML) are assayed through simulation. It is discerned that MUD provides remarkable amelioration in terms of mitigating MAI for coded signals on MIMO channels.
Thursday, March 20, 2008
Hav u heard abt MIMO ?
Now that i did say im busy with my project thot that i mite as well write a bit abt wat it is all abt...not the entire cos it will be too much in one gulp. I'll give an intro. So here goes...
Have u heard of 2G mobiles. Well all of us were using them once upon a time. Its nothing but the first model mobiles all of us had, some even have now...the most familiar among it being the nokia 1100....ok so wat abt 2.5G...that includes a mobile enabled with GPRS. So is that the final one. Come on technology is ever evolving, will it stop with 2.5G. So we have the 3G mobiles. Now wat falls under that. Simple its the CDMA technology we all now, thats now implemented in India. So where do i come? Im researching in 4G communication. Know wat that means. Im into research and thats wer MIMO comes. Multi Input Multi Output deals with having multiple antennas at the transmitter and receiver. I cant make it more simpler. And my project is on the performance evaluation of these systems with more concentration on the receiver side. Im dealing with multistage receivers and using coded signals. We use Space Time Block Codes to code the signals and 2 stages of receivers are considered- Nulling and Cancellation. I guess this is more than enough terms for the first portion. More to come...Wait n watch.
Have u heard of 2G mobiles. Well all of us were using them once upon a time. Its nothing but the first model mobiles all of us had, some even have now...the most familiar among it being the nokia 1100....ok so wat abt 2.5G...that includes a mobile enabled with GPRS. So is that the final one. Come on technology is ever evolving, will it stop with 2.5G. So we have the 3G mobiles. Now wat falls under that. Simple its the CDMA technology we all now, thats now implemented in India. So where do i come? Im researching in 4G communication. Know wat that means. Im into research and thats wer MIMO comes. Multi Input Multi Output deals with having multiple antennas at the transmitter and receiver. I cant make it more simpler. And my project is on the performance evaluation of these systems with more concentration on the receiver side. Im dealing with multistage receivers and using coded signals. We use Space Time Block Codes to code the signals and 2 stages of receivers are considered- Nulling and Cancellation. I guess this is more than enough terms for the first portion. More to come...Wait n watch.
Pisces
Being a piscean has its own charm. Hey that wasnt said by me. Many have the same view and so I wud like to put down few points on this wonderful sun sign. The characters et al. So here goes: Very few pisceans can stand being confined for long in one place. Creative, artistic, leisurel and estoric (hmmm) wid very little worldly ambition and even less attraction to wealth. They just want to live wid no care on wat tmrw holds for them adn wont strugle their way upstream. They instead swim with the current (Boring is it?). But here comes the best part. One will be impressed by the piscean charm (I told u) of manner and lazy good nature. They will rarely be aroused to violent reactions. But once they are they can be bitingly sarcastic. However they find themselves coiling back to the calm waters soon after. They know the reality but prefer to stay in their own sweet, gentle world. And here comes the important part, the one i see everywer: Most of them have possibilities of wasting time day-dreaming or going thru stuff wich is entirely useless and an unreasonable waste of time. They are quite intuitive and hav unusual talents that may surface even to their surprise. Pisces represents death or eternity of the soul. It is a composite of all that has gone before and hence u can see charcteristics of all the signs influencing them. It mite not be possible to fix one character as that belongin to these diverse ppl who may change wid every passing time to the character best suited to them. Leave them in their home ground and see the lovely pisceans coming up and exhibiting the characters all so spl to them.
Tuesday, March 18, 2008
Im not dead !!
My last post was on feb 29th. One whole month back...well this is just to say that im not dead. Still hale and healthy. I had too many things in my head and hand last month that i jus cud not make the time. So wait for me while I get back soon. Jus l;et my project get over. That will be 18th april. And den i'll come on and off. But fear not cos after the 6th of May im here for keeps. So till den signing off from here...its moi...Maria...take care....love ya all...
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