Flowgraph output

FSK Demodulation in GNU Radio

Frequency Modulation (FM) is one of the oldest communication techniques for high fidelity transmission. Its digital counterpart, Frequency Shift Keying (FSK), also plays a crucial role in applications requiring low receiver complexity. In an FSK scheme, digital information is transmitted by changing the frequency of a carrier signal. It can also be mixed with Chirp Spread Spectrum (CSS) for low-power long-range communication as used in LoRa PHY. Binary FSK Binary FSK (BFSK) is the simplest form of FSK where the two bits 0 and 1 correspond to two distinct carrier frequencies $F_0$ and $F_1$ to be sent over the air.

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Beamforming in multi-user vs massive MIMO systems

Zero-Forcing (ZF) Detection in Massive MIMO Systems

Massive MIMO is one of the defining technologies in 5G cellular systems. In a previous article, we have described spatial matched filtering (or maximum ratio) as the simplest algorithm for signal detection. Here, we explain another linear technique, known as Zero-Forcing (ZF), for this purpose. It was described before in the context of simple MIMO systems here. Background Consider the block diagram for uplink of a massive MIMO system as drawn below with $N_B$ base station antennas and $K$ mobiler terminals. It is evident that the cumulative signal at each base station antenna $j$ is a summation of signals arriving

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Antenna Arrays: Whole is More than its Parts

In a previous article, we described how multiples antennas can be viewed as sampling the signal in space domain in a direct analogy to sampling the signal in time domain. Filters in discrete-time domain are usually defined by numerical values in the time axis. Space allows three-dimensional freedom. A filter in discrete space can have its elements placed anywhere in the space. This sounds very complicated! But we will show it is not. A Simple Time Domain Filter: 2-Tap FIR The simplest discrete FIR filter has only two samples of unit magnitude. Assuming unit magnitude and zero phase for both

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A timing locked loop with a Gardner TED converging to the steady state value for a square-root raised cosine pulse with excess bandwidth 0.4

Gardner Timing Error Detector: A Non-Data-Aided Version of Zero-Crossing Timing Error Detectors

Timing synchronization plays the role of the heart of a digital communication system. We have already seen how a timing locked loop, commonly known as symbol timing PLL, works where I explained the intuition behind the maximum likelihood Timing Error Detector (TED). A simplified version of maximum likelihood TED, known as Early-Late Timing Error Detector, was also covered before. Today we discuss a different timing synchronization philosophy that is based on zero-crossing principle. It is commonly known as Gardner timing recovery. Background Before we start this topic, I recommend that you read about Pulse Amplitude Modulation (PAM) for an introduction

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At the boundary of two OFDM symbols, pulse shaping smoothes the edges, resulting in the avoidance of spectral regrowth

Windowing an OFDM Signal in Time Domain

Orthogonal Frequency Division Multiplexing (OFDM) has been introduced in a previous article as a technique suitable for high data-rate transmissions over a wireless channel. The two main advantages I mentioned were as follows: Simple one-tap equalization, and Ability to slice the spectrum and utilize each slice in an independent manner. Due to these advantages, it was adopted as the preferred modulation in WiFi and 4G-LTE systems. The interesting part is that while many new waveforms were proposed to replace it in 5G NR, OFDM was still the modulation of choice for both downlink and uplink directions with some minor changes.

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