Milestone 1000+ subscribers 1100+ comments

Those who are regular visitors to dsplog.com might have noticed the small FeedBurner chicklet on the side showing subscriber count showing 1000+ subscribers. Its a nice milestone to reach, one that looked so distant when I wrote the first post stating the objective of this blog on 26th February 2007. We now have around 86 articles with 1100+ comments.

dashboard on dsplog.com
dashboard on dsplog.com

Brief History

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The rate of new subscribers improved dramatically once I introduced the free e-Book in October of 2008.

Joining the email subscription list entitles you to receive the free e-Book on Probability of Error for BPSK/QPSK/16QAM/16PSK/64QAM in AWGN.

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Future

While writing the posts, making the simulations to work and responding to all those comments, I learned a lot over the last two years. The signalprocessing for wireless comunication is a vast area and we have only just briefly started. I hope to continue to discuss topic relavent to signal processing for comuniction.

I am hoping that reaching the next 1000 subscribers wont take another two years, and for achieveing that I need your help. If each of you can tell atleast five of your friends/colleagues about this blog, it will go a long way in spreading the word about the blog. Thanks in advance.

Other thoughts

Over the past 6 to 8 weeks, I know that am guilty of not keeping up with the one past per week target which I have set myself nor am able to respond to comments within 2-3 days. I am not able to squeeze sufficient time for blogging after office work and parenting. I hope to come back to one post per week cycle from the second week of April 2009.

Alamouti STBC with 2 receive antenna

In the past, we had discussed two transmit, one receive antenna Alamouti Space Time Block Coding (STBC) scheme. In this post, lets us discuss the impact of having two antennas at the receiver. For the discussion, we will assume that the channel is a flat fading Rayleigh multipath channel and the modulation is BPSK.

Continue reading “Alamouti STBC with 2 receive antenna”

Approximate Vector Magnitude Computation

In this post, let us discuss a simple implementation friendly scheme for computing the absolute value of a complex number . The technique called (alpha Max + beta Min) algorithm is discussed in Chapter 13.2 of Understanding Digital Signal Processing, Richard Lyons and is also available online at Digital Signal Processing Tricks – High-speed vector magnitude approximation

The magnitude of a complex number is

.

The simplified computation of the absolute value is

where

.

Continue reading “Approximate Vector Magnitude Computation”

Derivation of BPSK BER in Rayleigh channel

This is a guest post by Jose Antonio Urigüen who is an Electrical and Electronic Engineer currently studying an MSc in Communications and Signal Processing at Imperial College in London. This guest post has been created due to his own curiosity when reviewing some concepts of BER for BPSK in Rayleigh channnel published in the dsplog.com

From the post on BER for BPSK in Rayleigh channnel, it was shown that, in the presence of channel , the effective bit energy to noise ratio is .

Continue reading “Derivation of BPSK BER in Rayleigh channel”

Viterbi decoder

Coding is a technique where redundancy is added to original bit sequence to increase the reliability of the communication. Lets discuss a simple binary convolutional coding scheme at the transmitter and the associated Viterbi (maximum likelihood) decoding scheme at the receiver.

Update: For some reason, the blog is unable to display the article which discuss both Convolutional coding and Viterbi decoding. As a work around, the article was broken upto into two posts.

This post descrbes the Viterbi decoding algorithm for a simple Binary Convolutional Code with rate 1/2, constraint length and having generator polynomial . For more details on the Binary convolutional code, please refer to the post – Convolutional code

Continue reading “Viterbi decoder”

Convolutional code

Coding is a technique where redundancy is added to original bit sequence to increase the reliability of the communication. In this article, lets discuss a simple binary convolutional coding scheme at the transmitter and the associated Viterbi (maximum likelihood) decoding scheme at the receiver.

Update: For some reason, the blog is unable to display the article which discuss both Convolutional coding and Viterbi decoding. As a work around, the article was broken upto into two posts. This post descrbes a simple Binary Convolutional Coding scheme. For details on the Viterbi decoding algorithm, please refer to the post – Viterbi decoder.

Chapter 8, Table 8.2-1 of Digital Communications by John Proakis lists the various rate 1/2 convolutional coding schemes. The simplest among them has constraint length with generator polynomial . There are three parameters which define the convolotional code:

Continue reading “Convolutional code”

MIMO with ML equalization

We have discussed quite a few receiver structures for a 2×2 MIMO channel namely,

(a) Zero Forcing (ZF) equalization

(b) Minimum Mean Square Error (MMSE) equalization

(c) Zero Forcing equalization with Successive Interference Cancellation (ZF-SIC)

(d) ZF-SIC with optimal ordering and

(e) MIMO with MMSE SIC and optimal ordering

From the above receiver structures, we saw that MMSE equalisation with optimally ordered Successive Interference Cancellation gave the best performance. In this post, we will discuss another receiver structure called Maximum Likelihood (ML) decoding which gives us an even better performance. We will assume that the channel is a flat fading Rayleigh multipath channel and the modulation is BPSK.

Continue reading “MIMO with ML equalization”

Join dspLog at Google FriendConnect

We have installed Google FriendConnect on dspLog.com. With Google Friend Connect, you can:

(a) You can interact with other members who have similiar interests. You will come to know the list of other sites (apart from dspLog.com) where the members have joined. You can add a member as a friend and so on.

(b) You can invite friends from orkut, Google Talk and other social networks and contact lists to join.

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If you wish to join dspLog community via FriendConnect, please click ‘Join this Site‘ button on the sidebar.

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MIMO with MMSE SIC and optimal ordering

This post attempts to build further on the MIMO equalization schemes which we have discussed –

(a) Minimum Mean Square Error (MMSE) equalization,

(b) Zero Forcing equalization with Successive Interference Cancellation (ZF-SIC) and

(c) ZF-SIC with optimal ordering.

We have learned that successive interference cancellation with optimal ordering improves the performance with Zero Forcing equalization. In this post, we extend the concept of successive interference cancellation to the MMSE equalization and simulate the performance. We will assume that the channel is a flat fading Rayleigh multipath channel and the modulation is BPSK.

Continue reading “MIMO with MMSE SIC and optimal ordering”

MIMO with ZF SIC and optimal ordering

In previous posts, we had discussed equalization of a 2×2 MIMO channel with Zero Forcing (ZF) equalization and later, Zero Forcing equalization with successive interference cancellation (ZF-SIC). In this post, we will explore a variant of ZF-SIC called Zero Forcing Successive Interference Cancellation with optimal ordering. We will assume that the channel is a flat fading Rayleigh multipath channel and the modulation is BPSK.

Continue reading “MIMO with ZF SIC and optimal ordering”