Kyungchun Lee

MIMO-assisted hard versus soft decoding-and-forwarding for network coding aided relaying systems

This paper proposes two types of new decoding algorithms for a network coding aided relaying (NCR) system, which adopts multiple antennas at both the transmitter and receiver. In the NCR system, the relay station (RS) decodes the data received from both the base station (BS) as well as from the mobile station (MS) and combines the decoded signals into a single data stream before forwarding it to both. In this paper, we consider the realistic scenario of encountering decoding errors at the RS, which results in erroneous forwarded data. Under this assumption, we derive decoding algorithms for both the BS and the MS in order to reduce the deleterious effects of imperfect decoding at the RS. We first propose a decoding algorithm for a hard decision based forwarding (HDF) system. Then, for the sake of achieving further performance improvements, we also employ soft decision forwarding (SDF) and propose a novel error model, which divides the error pattern into two components: hard and soft errors. Given this error model, we then modify the HDF decoder for employment in SDF systems. We also derive estimation algorithms for their parameters that are required for the efficient operation of the proposed decoders. Our simulation results show that the proposed algorithms provide substantial performance improvements in terms of the attainable packet error rate as a benefit of our more accurate error model.

Optimal Lattice-Reduction Aided Successive Interference Cancellation for MIMO Systems

In this letter, we investigated the optimal minimum-mean-squared-error (MMSE) based successive interference cancellation (SIC) strategy designed for lattice-reduction aided multiple-input multiple-output (MIMO) detectors. For the sake of generating the MMSE-based MIMO symbol estimate at each SIC detection stage, we model the so-called effective symbols generated with the aid of lattice-reduction as joint Gaussian distributed random variables. However, after lattice-reduction, the effective symbols become correlated and exhibit a non-zero mean. Hence, we derive the optimal MMSE SIC detector, which updates the mean and variance of the effective symbols at each SIC detection stage. As a result, the proposed detector achieves a better performance compared to its counterpart dispensing with updating the mean and variance, and performs close to the maximum likelihood detector.

Symbol detection in V-BLAST architectures under channel estimation errors

We introduce a modified vertical Bell laboratories layered space-time (V-BLAST) detection algorithm to reduce unexpected effects of the channel estimation errors. Assuming that the channel estimation errors are independent and identically distributed Gaussian random variables, we derive a better nulling weight, which minimizes the power of various terms generated by the channel estimation errors. The symbol ordering operation is also modified by choosing the minimum mean-square error symbol at each iteration. The proposed detection algorithm requires the knowledge of channel estimation errors variance, but its performance is robust to the inaccurate estimation of it. The simulation results show that the performance of the proposed algorithm is superior to that of the conventional V-BLAST detection algorithm when channel estimation errors exist

Zero-Forcing Based Two-phase Relaying

In cellular mobile communication systems, the link performance can be remarkably improved by deploying relays between the base station and the mobile station. In this paper we propose an efficient duplexing scheme so that both spatial and temporal gain by adding relays can be increased. Using the proposed relaying scheme, the conventional system of four-phase relaying can be simplified to a two-phase relaying system and the additional resource consumption due to relays can be minimized. We show the capacity gain for cell edge users with numerical results.

A MIMO Antenna Structure that Combines Transmit Beamforming and Spatial Multiplexing

We propose a new closed-loop MIMO (Multiple- Input Multiple-Output) signal processing scheme that combines transmit beamforming and spatial multiplexing in Rayleigh frequency-flat fading channel environment. Diversity gain is achieved by beamforming, and multiplexing gain by spatial multi- plexing. The proposed scheme is particularly useful for downlink communication, where the number of transmit antennas at the base station is greater than the number of receive antennas at the mobile. Beamforming weight vectors are computed at the receiver using the estimated channel matrix and are sent to the transmitter. The computation is based on the mutual information maximization criterion which reduces to a symmetric eigenvalue problem. The BER (Bit Error Rate) performance comparisons with other known schemes are also presented for the cases of the ML (Maximum Likelihood) decoding and the MMSE (Minimum Mean-Squared Error) nulling and ordered-cancellation decod- ing, through extensive Monte-Carlo simulation. The simulation results show that the proposed scheme has lower BER than the other schemes.

ML Symbol Detection Based on the Shortest Path Algorithm for MIMO Systems

This paper presents a new maximum likelihood (ML) symbol detection algorithm for multiple-input multiple-output (MIMO) systems. To achieve the ML performance with low complexity, we search the integer points corresponding to symbol vectors in increasing order of the distance from the unconstrained least-squares solution. For each integer point, we test if it is the ML solution, and continue the integer point search until one of searched points is determined to be the ML solution. We present an efficient iterative search strategy, which is based on the shortest path algorithm for a graph. The simulation results show that the proposed algorithm has the lower complexity compared to the sphere decoding for channel matrices having low condition numbers. For further complexity reduction, we propose to use scaling, lattice-reduction, and regularization techniques. By applying these techniques, the computational complexity of proposed algorithm is reduced significantly when the channel matrix has a high condition number.

Frequency-Offset Estimation for MIMO and OFDM Systems Using Orthogonal Training Sequences

We propose a training-sequence-based frequency-offset estimator for a multiple transmit-and-receive antenna system in frequency-flat fading channels. The estimator is based on the maximum likelihood (ML) criterion and does not require channel information. To reduce the computational load, they propose to use special training sequences-the periodic orthogonal codes. Using these codes, we get a closed form estimator which requires much lower computational load (some additions and multiplications). For the high signal-to-noise ratio and small frequency offset, the proposed estimator achieves the performance of the optimal ML estimator, which locates the peak of the likelihood function. We also apply the proposed estimator to a multiple antenna system in frequency-selective channels and an orthogonal-frequency-division-multiplexing system. With theoretical analysis and simulations, we evaluate the performance of the proposed estimator

Resource-efficient wireless relaying protocols

Relay-aided communication is considered one of the key techniques to achieve high throughput at low cost in future wireless systems. However, when transmitting signals via a relay, additional time slots, antennas, or frequency slots are required, which may erode the potential gain of relay-aided systems. In this article various approaches to creating relay-aided systems are reviewed. The advantages and disadvantages of various relaying schemes are compared in terms of their slot efficiency, error rate performance, and feasibility. Our detailed comparisons and the numerical results indicate that the specific family of network coding aided relaying protocols constitutes one of the most promising solutions. We conclude this article by listing a number of open problems.

On the interference nulling operation of the V-BLAST under channel estimation errors

We propose a new interference nulling operation in V-BLAST (Vertical Bell Laboratories Layered Space Time) to reduce unexpected effects by the channel estimation errors. Assuming that the channel estimation is performed by pseudo-inverse of orthogonal or non-orthogonal training sequence matrix, we derive a better nulling vector which minimizes the power of various terms generated by the channel estimation errors. With simulations, we test the performance of the proposed algorithm.

Iterative Detection and Decoding for Hard-Decision Forwarding Aided Cooperative Spatial Multiplexing

In this paper, the optimal decoding strategy for cooperative spatial multiplexing (CSM) aided systems is derived. In CSM systems, the multiple relay stations (RSs), which compose a virtual antenna array (VAA), independently decode the packets received from the mobile stations (MS) and forward them to the base station (BS). When the BS decodes the signal forwarded from the RSs, the potential decoding errors encountered at the RSs will result in erroneous forwarding, but their effects are mitigated by the proposed solution. Our simulation results show that when the direct link has a significantly higher signal-to-noise ratio than the relay link, the proposed decoding algorithm achieves an approximately 3 dB better performance than conventional CSM, which does not consider the deleterious effects of erroneous forwarding from the RSs.