Abstract:
Rapid innovations in the fifth generation (5G) net-works have unveiled new challenges, mainly the transmission rate maximization. One of the most promising key technologi...Show MoreMetadata
Abstract:
Rapid innovations in the fifth generation (5G) net-works have unveiled new challenges, mainly the transmission rate maximization. One of the most promising key technologies for the upcoming 5G communication systems is massive multiple input multiple output (MIMO) that has been proven to boost the spectral efficiency and ensure a better system capacity. In fact, deploying a large number of transmit and receive antennas in MIMO networks can enhance the system performance. Nevertheless, the uplink signal detection still be very challenging in massive MIMO networks. In this paper, we adopt a massive MIMO scenario and we introduce a weighted Kalman uplink detection approach that is able to improve the system performance in terms of the bit error rate (BER) when using a large number of receive antennas. Simulations results confirm that the proposed algorithm performs better than Minimum Mean Square Error (MMSE) and Kalman filter detectors, especially for medium and high signal-to-noise ratio (SNR).
Published in: 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
Date of Conference: 17-19 September 2020
Date Added to IEEE Xplore: 28 October 2020
ISBN Information:
Electronic ISSN: 1847-358X
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- IEEE Keywords
- Index Terms
- Signal-to-noise ,
- Mean Square Error ,
- Simulation Results ,
- System Performance ,
- Detection Approach ,
- Kalman Filter ,
- Multiple-input Multiple-output ,
- Minimum Mean ,
- Bit Error Rate ,
- Bit Error ,
- Minimum Mean Square Error ,
- Minimum Mean Square ,
- Detection Methods ,
- Estimation Error ,
- Additive Noise ,
- Global Positioning System ,
- Carrier Frequency ,
- Base Station ,
- Dirac Delta ,
- Bit Error Rate Performance ,
- Error Covariance ,
- Kalman Gain ,
- Multiplexing Gain ,
- High Signal-to-noise Ratio ,
- Fading Channel ,
- Zero-forcing ,
- Rayleigh Fading Channel ,
- Robot Motion ,
- Update Phase
- Author Keywords
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Signal-to-noise ,
- Mean Square Error ,
- Simulation Results ,
- System Performance ,
- Detection Approach ,
- Kalman Filter ,
- Multiple-input Multiple-output ,
- Minimum Mean ,
- Bit Error Rate ,
- Bit Error ,
- Minimum Mean Square Error ,
- Minimum Mean Square ,
- Detection Methods ,
- Estimation Error ,
- Additive Noise ,
- Global Positioning System ,
- Carrier Frequency ,
- Base Station ,
- Dirac Delta ,
- Bit Error Rate Performance ,
- Error Covariance ,
- Kalman Gain ,
- Multiplexing Gain ,
- High Signal-to-noise Ratio ,
- Fading Channel ,
- Zero-forcing ,
- Rayleigh Fading Channel ,
- Robot Motion ,
- Update Phase
- Author Keywords
