LTE – Page 3 – RAYmaps

January 6, 2012June 7, 2012Channel Modeling, LTE

WINNER-II Path Loss Model

In simple terms the path loss is the difference between the transmitted power and the received power of a wireless communication system. This may range from tens of dB to more than a 100 dB e.g. if the transmitted power of a wireless communication system is 30 dBm and the received power is -90 dBm then the path loss is calculated as 30-(-90)=120 dB. Path loss is sometimes categorized as a large scale effect (in contrast to fading which is a small scale effect). According to the WINNER-II model the path loss can be calculated as: Here d is the […]

December 15, 2011December 27, 2011Capacity, LTE

Soft Frequency Reuse in LTE

Frequency Reuse is a well known concept that has been applied to wireless systems over the past two decades e.g. in GSM systems. As the name suggests Frequency Reuse implies using the same frequencies over different geographical areas. If we have a 25MHz band then we can have 125 GSM channels and 125*8=1000 time multiplexed users in a given geographical area. Now if we want to increase the number of users we would have to reuse the same frequency band in a geographically separated area. The technique usually adopted is to use a fraction of the total frequency band in […]

December 8, 2011June 4, 2014BER Performance, LTE, WiMAX

QAM Theoretical BER in AWGN

Quadrature Amplitude Modulation (QAM) is an important modulation scheme as it allows for higher data rates and spectral efficiencies. The bit error rate (BER) of QAM can be calculated through Monte Carlo simulations. However this becomes quite complex as the constellation size of the modulation schemes increases. Therefore a theoretical approach is sometimes preferred. The BER for Gray coded QAM, for even number of bits per symbol, is shown below. Gray coding ensures that a symbol error results in a single bit error. The code for calculating the theoretical QAM BER for k even (even number of bits per symbol) […]

November 25, 2011April 27, 2012Capacity, LTE, WiMAX

MIMO Capacity in a Fading Environment

The Shannon Capacity of a channel is the data rate that can be achieved over a given bandwidth (BW) and at a particular signal to noise ratio (SNR) with diminishing bit error rate (BER). This has been discussed in an earlier post for the case of SISO channel and additive white Gaussian noise (AWGN). For a MIMO fading channel the capacity with channel not known to the transmitter is given as (both sides have been normalized by the bandwidth [1]): Shannon Capacity of a MIMO Channel where NT is the number of transmit antennas, NR is the number of receive […]

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 […]

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 […]