Precoding
and Detection Algorithms
Precoding and detection algorithms are fundamental approaches to mitigating interference at the transmitter and receiver of modern wireless communication systems. In 5G systems, the heterogeneity and architecture of networks and the increasing levels of interference pose challenges for the design precoding and detection algorithms.
In particular, precoding algorithms must have access to the channels of all users in the system in order to perform interference mitigation, which is often carried out with the help of signal processing transformations. Among the existing precoders are vector perturbation, Tomlinson-Harashima and linear techniques, which exhibit different performance complexity trade-offs. Key problems in the design of precoders for 5G networks include the limitation of existing signal processing algorithms which are not scalable, the hardware impairments, inaccurate channel state information across networks with small cells, network MIMO concepts and users with mobility. In our 5G lab, we look at innovative solutions to the problems encountered in the design of precoders, namely:
o Low-complexity precoding strategies
o Robust precoding algorithms
o RF-aware precoding designs
o Pilot contamination
In the case of detection algorithms, the receiver must perform synchronization, channel estimation prior interference mitigation, which is often carried out with the help of either lattice searches or receive filters. Among the most effective detection algorithms are maximum likelihood detectors, sphere decoders, lattice-reduction techniques, decision-feedback schemes, successive interference cancellation and linear techniques, which exhibit different performance complexity trade-offs. Key problems in the design of detectors for 5G networks include the limitation of existing signal processing algorithms which are not scalable to large-scale systems, hardware impairments, inaccurate channel state information across networks with small cells, network MIMO concepts and users with mobility and decoding delay when iterative detection and decoding algorithms are employed. In our 5G lab, we look at innovative solutions to the problems in the design of detectors, namely:
o Low-complexity detection algorithms
o Low-delay iterative detection and decoding techniques
o RF-aware detection algorithms
Selected Publications:
T. L.
Marzetta, Noncooperative Cellular Wireless with
Unlimited Numbers of Base Station Antennas, IEEE Trans. Wireless Communications,
vol. 9, no. 11, pp. 3590-3600, Nov. 2010.
R. C. de Lamare,
"Massive MIMO Systems: Signal Processing Challenges and Future
Trends", URSI Radio Science Bulletin, 2013. pdf presentation
R.
C. de Lamare and R. Sampaio-Neto,
Signal Detection and Parameter Estimation in Massive MIMO Systems, Signal
Processing and Applications, Elsevier (tentative), 2015. pdf
W. Zhang, C. Pan, M. Chen, R. C. de Lamare and J. Dai, “Large-Scale Antenna Systems with UL/DL
Hardware Mismatch: Achievable Rates Analysis and Calibration”, IEEE
Transactions on Communications, 2015. pdf
L. Zhang, Y. Cai, R. C. de Lamare, M. Zhao,
"Robust Multi-Branch
Tomlinson-Harashima Precoding Design in
Amplify-and-Forward MIMO Relay Systems, IEEE Transactions on Communications,
2014. pdf
K. Zu, R. C. de Lamare and M. Haardt, "Multi-Branch
Tomlinson-Harashima Precoding Design for MU-MIMO
Systems: Theory and Algorithms", IEEE Transactions on Communications,
2014. pdf
K. Zu, R. C. de Lamare and M. Haardt,
"Generalized Design of Low-Complexity Block Diagonalization Type Precoding
Algorithms for Multiuser MIMO Systems", IEEE Transactions on
Communications, 2013. pdf
P. Li and R. C. de Lamare,
"Distributed Iterative Detection with Reduced Message Passing for
Networked MIMO Cellular Systems", IEEE Transactions on Vehicular
Technology, 2014. pdf
R. C. de Lamare,
"Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection
Algorithms for Multi-Antenna Systems", IEEE Transactions on Wireless
Communications, October 2013. pdf
P. Li, R. C. de Lamare and
R. Fa, “Multiple Feedback Successive Interference Cancellation Detection for
Multiuser MIMO Systems”, IEEE Transactions on Wireless Communications, 2011. pdf
Matlab Codes and Tools:
Precoding algorithms – codes
Detection algorithms - codes
LDPC-coded detection algorithms - codes