Tag: SINR

Capacity, 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 […]

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Channel Capacity, LTE

Average Cell Throughput Calculations for LTE

Average Cell Throughput requires the following simulation results • Average SINR distribution table (system level result), which provides the SINR probability • Average throughput or spectral efficiency versus average SINR table (link level result) For urban channel model and a fixed inter-site distance of 1732m,downlink throughput for LTE for different values of SINR is shown below. MCS vs SINR Average Cell Throughput=Σ(Pi*Ri) where Pi=Probability of occurrence of a specific SINR value at cell edge obtained using simulations Ri=Average throughput corresponding to SINR range Let us consider the following distribution for the SINR at the cell edge: P1=0.5 (SINR=1.50-3.50 dB) P2=0.25 […]

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Capacity, WCDMA

WCDMA Capacity (Mbps)

The capacity of any wireless communication channel is given by the well known Shannon Capacity Theorem: C=B*log2(1+SNR) or C=B*log2(1+P/(NoB)) where C is the capacity of the channel in bits/sec, P in the noise power in Watts, No is the noise power spectral density in Watts/Hz and B is the channel bandwidth in Hz. It is obvious that the channel capacity increases with increase in signal power. However, the relationship with bandwidth is a bit complicated. The increase in bandwidth decreases the SNR (keeping the signal power and noise power spectral density same). Therefore the capacity does not increase linearly with […]

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