RAYmaps – Page 11 – <<<All Things Wireless>>>

November 13, 2011November 18, 2011LTE, WCDMA, WiMAX

CDMA vs OFDMA

Property CDMA OFDMA 1. Channel bandwidth Full system bandwidth Variable system bandwidth to accommodate users with different data rates, 1.25, 2.50, 5.00, 10.00, 15.00 and 20.00 MHz, actual transmission bandwidth is a bit lower than this 2. Frequency-selective scheduling Not possible A key advantage of OFDMA, although it requires accurate real-time feedback of channel conditions from receiver to transmitter 3. Symbol period Very short—inverse of the system bandwidth Very long—defined by subcarrier spacing and independent of system bandwidth 4. Equalization Complicated time domain equalization Simple frequency domain equalization 5. Resistance to mulitpath Rake receiver can combine various multipath components Highly resistant […]

November 7, 2011November 15, 2011LTE

Peak to Average Power Ratio (PAPR)

Peak to Average Power Ratio (PAPR) as the name suggests is the ratio of peak signal power to the average signal power and has received considerable attention in the context of multicarrier signals like OFDM which exhibit a high PAPR. The down side of this high PAPR is that the power amplifier in the transmitter is operated at a relatively lower power level so that the peaks in the signal are not distorted by the saturating amplifier. This is called the amplifier backoff and it plays an important part in wireless system design. Power Amplifier Input Output Behavior The reason […]

November 1, 2011June 16, 2014Channel Modeling

Computationally Efficient Rayleigh Fading Simulator

We had previously presented a method of generating a temporally correlated Rayleigh fading sequence. This was based on Smith’s fading simulator which was based on Clark and Gan’s fading model. We now present a highly efficient method of generating a correlated Rayleigh fading sequence, which has been adapted from Young and Beaulieu’s technique [1]. The architecture of this fading simulator is shown below. This method essentially involves five steps. 1. Generate two Gaussian random sequences of length N each. 2. Multiply these sequences by the square root of Doppler Spectrum S=1.5./(pi*fm*sqrt(1-(f/fm).^2). 3. Add the two sequences in quadrature with each other […]

October 28, 2011November 17, 2011LTE

LTE Resource Allocation in Time-Frequency Plane

The LTE standard defines a resource allocation structure in time and frequency domains. If the spatial domain is also considered the resource allocation structure actually becomes a 3-dimensional arrangment. We will ignore the spatial domain for now and focus on the time-frequency plane. In the time domain the LTE transmissions are organized into frames of 10 msec length. Each frame is composed of 10 subframes of 1 msec duration. Each subframe is made up of two equal sized slots of 0.5 msec each. Each slot is composed of 7 or 6 OFDM symbols depending upon whether a short or long […]

October 21, 2011June 7, 2012Channel Modeling, LTE, WiMAX

A Rayleigh Fading Simulator with Temporal and Spatial Correlation

Just to recap, building an LTE fading simulator with the desired temporal and spatial correlation is a three step procedure. 1. Generate Rayleigh fading sequences using Smith’s method which is based on Clarke and Gan’s fading model. 2. Introduce spatial correlation based upon the spatial correlation matrices defined in 3GPP 36.101. 3. Use these spatially and temporally correlated sequences as the filter taps for the LTE channel models. We have already discussed step 1 and 3 in our previous posts. We now focus on step 2, generating spatially correlated channels coefficients. 3GPP has defined spatial correlation matrices for the Node-B […]

October 21, 2011November 15, 2011Channel Modeling, LTE, WiMAX

Building an LTE Channel Simulator

As discussed previously building an LTE fading simulator is a three step procedure. 1. Generate a temporally correlated Rayleigh fading sequence. This step would be repeated for each channel tap and transmit receive antenna combination e.g. for a 2×2 MIMO system and EPA channel model with 7 taps the number of fading sequences to be generated is 4×7=28. The temporal correlation of these fading sequences is controlled by the Doppler frequency. A higher Doppler frequency results in faster channel variations and vice versa. 2. Introduce spatial correlation between the parallel paths e.g. for a 2×2 MIMO system a 4×4 antenna […]

October 19, 2011November 15, 2011BER Performance, Channel Modeling, LTE, WiMAX

Can We Do Without a Cyclic Prefix

Have you ever thought that Cyclic Prefix in OFDM is just a gimmick and we could do equally well by using a guard period i.e. a period of no transmission between two OFDM symbols. Well, one way to find out if this is true is by running a bit error rate simulation with and without a cyclic prefix (only a vacant guard period). We use the 64-QAM OFDM simulation that we developed previously. The channel is modeled as 7-tap FIR filter with each tap having a Rayleigh distribution. BER with and without Cyclic Prefix We simulate the case of a […]

October 12, 2011June 24, 2020Channel Modeling, LTE, WiMAX

LTE Fading Simulator

As discussed previously an LTE channel can be modeled as an FIR filter. The filter taps are described by the EPA, EVA and ETU channel models. If x(k) is the original signal then the signal at the output of the FIR filter y(k) is given as: y(k)=x(k)*c(0)+x(k-1)*c(1)+…..+x(k-L+2)*c(L-2)+x(k-L+1)*c(L-1) Since the wireless channel is time varying the channel taps c(0) c(1)…..c(L-1) are also time varying with either Rayleigh or Rician distribution. It is quite easy to generate Rayleigh random variables with the desired power and distribution, however, when these Rayleigh random variables are required to have temporal correlation the process becomes a […]

October 7, 2011November 21, 2013Channel Modeling, LTE, WiMAX

LTE Multipath Channel Models

When a wireless signal travels from a transmitter to a receiver it follows multiple paths. The signal may travel directly following the line of sight between the transmitter and receiver, it may bounce off the ground and reach the receiver or it may be reflected by multiple buildings on the way to the receiver. When these copies of the same signal arrive at the receiver they are delayed and attenuated based upon the path length that they have followed and various other factors. A well known technique to model such a wireless channel is to model it as an FIR […]