Standards – Page 3

August 24, 2017August 28, 2017BER Performance, Channel Modeling, LTE, WiMAX

BER for BPSK-OFDM in Frequency Selective Channel

As the data rates supported by wireless networks continue to rise the bandwidth requirements also continue to increase (although spectral efficiency has also improved). Remember GSM technology which supported 125 channels of 200KHz each, which was further divided among eight users using TDMA. Move on to LTE where the channel bandwidth could be as high as 20MHz (1.4MHz, 3MHz, 5MHz, 10MHz, 15MHz and 20MHz are standardized). This advancement poses a unique challenge referred to as frequency selective fading. This means that different parts of the signal spectrum would see a different channel (different amplitude and different phase offset). Look at […]

August 22, 2017August 22, 2017Channel Modeling, Fundamentals, LTE

Rayleigh Fading Envelope Generation – Python

When wireless signals travel from a transmitter to a receiver they do so after reflection, refraction, diffraction and scattering from the environment. Very rarely is there a direct line of sight (LOS) between the transmitter and receiver. Thus multiple time delayed copies of the signal reach the receiver that combine constructively and destructively. In a sense the channel acts as an FIR (finite impulse response) filter. Furthermore since the transmitter or receiver may be in motion the amplitude and phase of these replicas varies with time. There are several methods to model the amplitude and phase of each of these […]

Eclipse

Eclipse 1.0 – A Paradigm Shift in RF Planning NEW: Simulation of a Moving Transmitter (such as a car) NEW: Simulation of a Moving Transmitter (such as a pedestrian) Radio frequency planning is an essential component of network planning, roll-out, up-gradation, expansion etc. Several methods can be adopted for this from something as simple as free space models, empirical path loss models to the significantly more complicated, time consuming and expensive drive testing. Drive testing gives very accurate results but these results can be rendered useless by changing the position of an antenna or the tilt or transmit power of […]

Udemy Course

Introduction to Wireless Communications • In this course you will learn the basic principles of wireless communications from 1G to 5G and beyond. You will learn about frequency reuse, capacity, channel coding, modulation and demodulation, OFDM, MIMO, and a host of other topics. • This course is for you if you are a student and have just started learning about wireless communications or if you are a guy in the field who wants to get a better handle on the fundamental concepts of wireless communications. Here is the link to the course.

October 1, 2014October 31, 2014Channel Modeling, Fundamentals, LTE

Modified Young’s Fading Simulator

In the previous posts we had discussed generation of a correlated Rayleigh fading sequence using Smith’s method [1] and Young’s modification of Smith’s method [2]. The main contribution of Young was that he proposed a mechanism where the number of IDFTs was reduced by half. This was achieved by first adding two length N IID zero mean Gaussian sequences filtered by the filter F[k] and then performing the IDFT on the resulting complex sequence. This was different to Smith’s method where the IDFT was performed simultaneously on two branches and then the outputs of these branches were added in quadrature […]

June 4, 2014November 17, 2019BER Performance, Fundamentals, LTE

Theoretical BER of M-QAM in Rayleigh Fading

We have previously discussed the Bit Error Rate of M-QAM in Rayleigh Fading using Monte Carlo Simulation. We now turn our attention to calculation of Bit Error Rate (BER) of M-QAM in Rayleigh fading using analytical techniques. In particular we look at the method used in MATLAB function berfading.m. In this function the BER of 4-QAM, 16-QAM and 64-QAM is calculated from series expressions having 1, 3 and 5 terms respectively. These are given below (M is the constellation size and must be a power of 2). if (M == 4) ber = 1/2 * ( 1 – sqrt(gamma_c/k./(1+gamma_c/k)) ); elseif […]

July 26, 2013October 4, 2020Fundamentals, LTE, Solar Energy, WiMAX

Sizing Up a Solar System for a Cellular Base Station

Many operators are thinking of moving from the main grid to alternative energy sources such as wind and solar. This is especially true in third world countries where electricity is not available 24/7 and is also very expensive. This has forced operators to switch their base stations to diesel generators (which is also a costly option). In this article we do a rough estimation of the size a solar system required to run a cellular base station. We start with the assumption that 20 Watts of power are transmitted from a single antenna of base station. For a 3 sector […]

April 9, 2013April 9, 2013Capacity, Fundamentals, LTE

Does Shannon Capacity Increase by Dividing a Frequency Band into Narrow Bins

Somebody recently asked me this question “Does Shannon Capacity Increase by Dividing a Frequency Band into Narrow Bins”. To be honest I was momentarily confused and thought that this may be the case since many of the modern Digital Communication Systems do use narrow frequency bins e.g. LTE. But on closer inspection I found that the Shannon Capacity does not change, in fact it remains exactly the same. Following is the reasoning for that. Shannon Capacity is calculated as: C=B*log2(1+SNR) or C=B*log2(1+P/(B*No)) Now if the bandwidth ‘B’ is divided into 10 equal blocks then the transmit power ‘P’ for each […]

May 22, 2012May 31, 2022BER Performance, Fundamentals, LTE, Modulation, WiMAX

M-QAM Bit Error Rate in Rayleigh Fading

We have previously discussed the bit error rate (BER) performance of M-QAM in AWGN. We now discuss the BER performance of M-QAM in Rayleigh fading. The one-tap Rayleigh fading channel is generated from two orthogonal Gaussian random variables with variance of 0.5 each. The complex random channel coefficient so generated has an amplitude which is Rayleigh distributed and a phase which is uniformly distributed. As usual the fading channel introduces a multiplicative effect whereas the AWGN is additive. The function “QAM_fading” has three inputs, ‘n_bits’, ‘M’, ‘EbNodB’ and one output ‘ber’. The inputs are the number of bits to be passed […]