Add to ORKGAn adaptive minimum bit error rate (MBER) linear multiuser detector (MUD) is proposed for DS-CDMA systems. Based on the approach of kernel density estimation for approximating the bit error rate (BER) from training data, a least mean squares (LMS) style adaptive algorithm is developed for training linear MUDs. Computer simulation results show that this adaptive MBER linear MUD outperforms two existing LMS-style adaptive MBER algorithms
Adaptive training of neural networks is typically done using some stochastic gradient algorithm that...
The paper investigates the application of an emerging learning technique, called support vector mach...
The well known code division multiple access maximum likelihood receiver (MF-ML) uses a bank of matc...
The problem of constructing adaptive minimum bit error rate (MBER) linear multiuser detectors is con...
An adaptive minimum symbol error rate (MSER) linear multiuser detector (MUD) is proposed for direct ...
The Minimum Bit Error Rate (MBER) linear MUDs considered are designed for the synchronous downlink o...
This paper proposes an adaptive Minimum Conditional Bit-ErrorRate (MCBER) Multi-User Detector (MUD) ...
An Adaptive minimum bit error rate (MBER) based linear multiuser detection scheme is proposed for an...
An Adaptive minimum bit error rate (MBER) based linear multiuser detection scheme is proposed for an...
The paper investigates the application of a recently introduced learning technique, called the relev...
A novel minimum bit-error rate (MBER) space–time-equalization (STE)-based multiuser detector (MUD) i...
A novel minimum bit-error rate (MBER) space–time equalization (STE)-based multiuser detector (MUD) i...
In the recent years, MIMO MC-CDMA techniques have been proposed in order to increase system capacity...
The paper investigates the application of a recently introduced learning technique, referred to as t...
This contribution investigates a space-time equalisation as-sisted multiuser detection scheme design...
Adaptive training of neural networks is typically done using some stochastic gradient algorithm that...
The paper investigates the application of an emerging learning technique, called support vector mach...
The well known code division multiple access maximum likelihood receiver (MF-ML) uses a bank of matc...
The problem of constructing adaptive minimum bit error rate (MBER) linear multiuser detectors is con...
An adaptive minimum symbol error rate (MSER) linear multiuser detector (MUD) is proposed for direct ...
The Minimum Bit Error Rate (MBER) linear MUDs considered are designed for the synchronous downlink o...
This paper proposes an adaptive Minimum Conditional Bit-ErrorRate (MCBER) Multi-User Detector (MUD) ...
An Adaptive minimum bit error rate (MBER) based linear multiuser detection scheme is proposed for an...
An Adaptive minimum bit error rate (MBER) based linear multiuser detection scheme is proposed for an...
The paper investigates the application of a recently introduced learning technique, called the relev...
A novel minimum bit-error rate (MBER) space–time-equalization (STE)-based multiuser detector (MUD) i...
A novel minimum bit-error rate (MBER) space–time equalization (STE)-based multiuser detector (MUD) i...
In the recent years, MIMO MC-CDMA techniques have been proposed in order to increase system capacity...
The paper investigates the application of a recently introduced learning technique, referred to as t...
This contribution investigates a space-time equalisation as-sisted multiuser detection scheme design...
Adaptive training of neural networks is typically done using some stochastic gradient algorithm that...
The paper investigates the application of an emerging learning technique, called support vector mach...
The well known code division multiple access maximum likelihood receiver (MF-ML) uses a bank of matc...