Wireless/SDR Archives | Page 8 of 21

A V-BLAST architecture for 4 Tx antennas

December 15, 2021 Wireless/SDR

V-BLAST with Successive Interference Cancelation

In the article on Zero-Forcing detector for MIMO receivers, we have seen that the performance of linear detectors is unsatisfactory for actual implementations of conventional MIMO systems. Their main attraction comes from their low computational complexity. To strike a nice balance between performance and complexity, a neat trick is employed by the algorithm known as Successive Interference Cancelation (SIC). The concept was devised by Gerard Foschini from Bell Labs, although it was not a new idea. Successive interference cancelation was already proposed for the detection algorithms in CDMA systems. Again, the fundamental idea was borrowed from decision feedback equalization schemes

October 31, 2020 Wireless/SDR

Mueller and Muller Timing Synchronization Algorithm

Proposed in 1976, Mueller and Muller algorithm is a timing synchronization technique that operates at symbol rate, as opposed to most other synchronization algorithms that require at least 2 samples/symbol such as early-late and Gardner timing error detectors. All of these are feedback techniques that operate within a PLL. Feedforward methods such as digital filter and square timing synchronization are also feasible due to powerful digital signal processing that avoids feedback problems such as hangups. The most confusing thing communication engineers and radio hobbyists find about Mueller and Muller algorithm algorithm is the cross product in its expression: matched filter

November 22, 2021 Wireless/SDR

Maximum Ratio Combining (MRC)

In the discussion on diversity, we described in detail the idea of space diversity through an example of Selection Combining (SC). Maximum Ratio Combining (MRC) is another space diversity scheme that embodies the concept behind generalized beamforming — the main technology in 5G cellular systems. Let us find out how. Setup Consider a wireless link with 2 Tx antenna and 2 (or more) Rx antennas as shown in the figure below. At each symbol time, a data symbol $s$ is transmitted which belongs to a Quadrature Amplitude Modulation (QAM) scheme. To focus on the events happening within one symbol time

January 20, 2022 Wireless/SDR

Least Mean Square (LMS) Equalizer – A Tutorial

The LMS algorithm was first proposed by Bernard Widrow (a professor at Stanford University) and his PhD student Ted Hoff (the architect of the first microprocessor) in the 1960s. Due to its simplicity and robustness, it has been the most widely used adaptive filtering algorithm in real applications. An LMS equalizer in communication system design is just one of those beautiful examples and its other applications include noise and echo cancellation, beamforming, neural networks and so on. Background The wireless channel is a source of severe distortion in the received (Rx) signal and our main task is to remove the

Odd symmetry around frequency points at half symbol rate adding up to a flat spectrum

February 29, 2024 DSP / Wireless/SDR

Proof of Poisson Sum Formula

The Poisson sum formula was discovered by the French mathematician and physicist Siméon Denis Poisson. It has several applications in digital signal processing, among which our concern is the periodic summation of modulated pulses in digital communication systems. Assume that $p(t)$ is a pulse shape (or any continuous-time function if you are not familiar with digital communications) and $P(f)$ is its Fourier Transform. The pulse is sampled at a rate of $f_s$ to produce its discrete version $p(nT_s)$ where $T_s=1/f_s$ is the duration between two samples. The Poisson summation formula relates these two quantities as \begin{equation}\label{equation-poisson-sum-formula} \frac{1}{T_s}\sum _{k=-\infty}^{\infty} P\left(f+\frac{k}{T_s}\right) =