Future 5G systems are expected to provide higher performance, partly unleashed by massive MIMO as well as tight cooperation like joint transmission CoMP. For paired and unpaired spectrum below 6 GHz RF-frequency bands, frequency division duplex as well as time division duplex (FDD/TDD) has to be supported. The use of large cooperation areas over several cells together with massive MIMO downlink...

Relay network was introduced to realize high-data rate transmission and high capacity with limited transmit power. However, channel state information (CSI) is needed due to the requirement from coherent data detection and the self-data removal at terminals in the two-way relay networks (TWRN). Traditional linear probing techniques are able to acquire the accurate CSI by using enough training se...

Single user channel estimation for the case of sparse channels with large delay spreads is addressed. In addition, practical pulse shapes are considered. In sparse channels, the eecient way to estimate the parameters is to estimate the continuous delays of each path, instead of using the typical discrete tapped delay line model. Due to the facts that the desired delays are not drawn from a simp...

Underwater acoustic channel (UAC) is one of the most challenging communication channels in the world, owing to its complex multi-path and absorption as well as variable ambient noise. Although adaptive equalization could effectively eliminate the inter-symbol interference (ISI) with the help of training sequences, the convergence rate of equalization in sparse UAC decreased remarkably. Besides,...

The leastmean p-power (LMP) is one of themost popular adaptive filtering algorithms. With a proper p value, the LMP can outperform the traditional least mean square (p = 2), especially under the impulsive noise environments. In sparse channel estimation, the unknown channel may have a sparse impulsive (or frequency) response. In this paper, our goal is to develop new LMP algorithms that can ada...

In this paper, a sparse set-membership proportionate normalized least mean square (SM-PNLMS) algorithm integrated with a correntropy induced metric (CIM) penalty is proposed for acoustic channel estimation and echo cancellation. The CIM is used for constructing a new cost function within the kernel framework. The proposed CIM penalized SM-PNLMS (CIMSM-PNLMS) algorithm is derived and analyzed in...