to download project abstract


In 4G, the using of Orthogonal Multiple Access techniques
(OMA) which does not fulfill the massive increase in Mobile networks
and also Increasing Technology like IOT. It was limiting the number of
users that can be supported by the number of orthogonal resources
available, as it was not fulfilling the exponential growth in Mobile
network like low latency, massive connectivity and energy efficiency
So to overcome the problems with OMA in 4G, In 5G NOMA was
implemented which overcomes problems to some extent. Like it uses
the same resource block. It transmit multiple users’ signals from the
transmitter to the receiver. By allowing multiple users to share the same
resource elements, be it in the time, frequency, space, or code domain.
The main advantage of NOMA is it uses power domain technique for
transmission of signals.
As NOMA is versatile technique. we can combine it with MIMO to
increase throughput as well as to increase spatial multiplexing to
increase achievable rates and diversity gain to decrease BER.
Our main aim of this project is to show the performance evaluation of
Multi-Input Multi-Output Non-Orthogonal Multiple Access (MIMO-
NOMA) for Next Generation Wireless Communication Systems. The
efficiency of the MIMO-NOMA technique over Non- Orthogonal Multiple
Access (NOMA) and Orthogonal Multiple Access (OMA) is examined by
using distinct parameters, in particular, Power Allocation (PA), Bit Error
Rate (BER), Outage Probability (OP), and Channel Capacity (CC).
A system model for MIMO is assumed for the two-user scenario. A
Rayleigh fading channel is assumed between the Transmitter and the
receiver. By using Rayleigh fading channel coefficients, calculated the

achievable rates and SNR equations for all techniques and then
compared each parameter with others.
Finally, the simulation results are provided to facilitate the performance
analysis of MIMO- NOMA for a next-generation wireless communication
system and also demonstrate the accuracy of the developed analytical


 Figure 3.1: NOMA transmission in DLmode
 Figure 3.2: NOMA in transmissionsection
 Figure 3.3: Decoding atreceiver
 Figure 3.4: MIMO-OMA Downlink systemmodel
 Figure 3.5: NOMA Downlink systemmodel
 Figure 3.6: MIMO Downlink systemmodel
 Figure 4.1: Power Allocation of MIMO-NOMA, NOMA, andOMA
 Figure 4.2: Channel Capacity of MIMO-NOMA, NOMA, andOMA
 Figure 4.3: Outage Probability of MIMO-NOMA, NOMA, andOMA
 Figure 4.4: Bit Error Rate of MIMO-NOMA, NOMA, andOMA


 OMA – Orthogonal MultipleAccess
 NOMA – Non – Orthogonal MultipleAccess
 MIMO-NOMA – Multiple Input Multiple
Output Non – Orthogonal
 SIC – Successive InterferenceCancellation
 SNR – Signal to NoiseRatio
 BER – Bit ErrorRate
 PA – PowerAllocation
 CC – ChannelCapacity
 OP – OutageProbability
 BEP – Bit ErrorProbability
 BS – BaseStation

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