In this study, the authors propose a low‐complexity symbol‐level combining (SLC) scheme for Chase combining‐based hybrid automatic repeat request in multiple‐input multiple‐output systems with a linear receiver. In the proposed scheme, a subset of all row vectors in the channel matrix is selected and used for combining and detection of retransmitted symbols, where the Sherman–Morrison–Woodbury lemma is applied for the utilisation of each selected row vector. Therefore, compared with the existing SLC schemes using the entire channel matrix, the proposed scheme can have an advantage in computational complexity. Furthermore, they develop a row vector selection criterion for the proposed SLC scheme to calculate the amount of the signal‐to‐interference‐noise ratio improvement based on the squared norm of each row vector with a significantly low complexity. Simulation results verify that compared with the existing SLC schemes, the proposed SLC scheme achieves similar or better error performance, while its computational complexity is lower or in the worst‐case similar.

The goal of this paper is to develop a hybrid automatic repeat request (HARQ) transmission state control algorithm for multiple-input multiple- output (MIMO) systems with interference cancellation (IC) detection to improve throughput. The HARQ transmission state is defined as the distribution of the initial packets and retransmission packets transmitted during a transmission time slot. In such a system, the retransmission packets normally have a lower error probability than initial packets. However, in terms of throughput, successful decoding of an initial packet is more rewarding than a retransmission packet. The proposed algorithm generates the transmission state in which initial packets and retransmission packets are sent together. The outcome is that it achieves a lower error probability for initial packets by exploiting the IC process and a significantly higher throughput than the conventional HARQ system, which is verified by simulation results.

A packet transmission strategy for multiple‐input multiple‐output systems with interference cancellation detection and hybrid automatic repeat request (HARQ) processes is proposed. The error probability and throughput of such a system depend on the choice of the set of packets to be transmitted in each packet transmission time interval, but there are no existing implementable strategies to optimise such choice of packets. In this study, the authors first define a concept of the effective interference level (EIL) and establish the relationship between the EIL and the effective signal‐to‐interference‐plus‐noise ratio. Then they show that choosing the set of packets that minimises the EIL successively from the lowest to the highest HARQ round leads to a lower packet error and higher system throughput than conventional HARQ, which is verified by simulation. Also, the proposed EIL‐based scheme uses only the acknowledgement feedback messages like a conventional HARQ scheme, because the number of HARQ rounds of each packet is the only required information to calculate the EIL. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of throughput with the signal‐to‐noise ratio gain of about 4.2 dB at maximum.

In this paper, detailed cross-correlation properties for Chu sequences are investigated. All possible values of the cross-correlation function of Chu sequences are derived for any given sequence length and lag, and the maximum magnitude distribution function$\rho _{N}(x)$, which is defined as the number of all Chu sequence pairs with length-$N$whose maximum magnitude of the cross-correlation function is${\sqrt {Nx}}$, is obtained. Also, good lower and upper bounds on the maximum number of available Chu sequences and a construction algorithm for the corresponding partial Chu sequence set are proposed when the maximum magnitude of the cross-correlation among the sequences is constrained. Numerical examples show that the proposed bounds are quite tight and the proposed construction algorithm is near-optimal up to fairly large value of$N$.

In this paper, an extended detection scheme is proposed for multiple-input multiple-output (MIMO) systems which employ partial incremental redundancy (IR) based hybrid automatic repeat request (HARQ). Based on the extended MIMO system model that interprets multiple retransmissions as a single transmission, the extended detection scheme estimates the entire transmitted symbols utilizing all information obtained up to the current retransmission. Compared with the conventional zero-forcing (ZF) detection scheme, the extended ZF detection scheme improves the post-processing signal-to-noise ratio (PSNR) of the newly transmitted symbols in every retransmission, as well as the repeatedly transmitted symbols. Simulation results verify that the extended detection scheme outperforms the conventional detection scheme. Simulation results also show that the extended minimum mean-square-error (MMSE) detection scheme can achieve a better error performance than the conventional maximum-likelihood (ML) detection scheme, and even the extended ZF detection scheme shows a comparable error performance to the conventional ML detection scheme.

In this paper, optimal pilot sequence designs for MIMO-OFDM systems in multi-cell environments are provided. The proposed multi-cell optimality criterion is to minimize the worst-case MSE of an LS-based channel estimator. To satisfy the multi-cell optimality, it is found that the pilot sequence set, having the perfect auto-correlation property, should meet the Welch bound and the maximum magnitude of the cross-correlation function should be further minimized. Multi-cell optimal pilot sequence designs for various pilot types and their DFT representations are proposed by adopting Chu sequences and a tight upper-bound on the maximum size of the pilot sequence set is derived for a given pilot sequence length and the maximum allowed cross-correlation value. Simulation results show that the proposed pilot sequences can improve both the MSE performance and the system performance in multi-cell environments.

In this paper, a low complexity ordered successive interference cancellation (OSIC) equalizer based on minimum-mean squared error (MMSE) criterion is proposed for suppressing intercarrier interference (ICI) caused by time-selective channels in OFDM systems. The proposed scheme exploits a low complexity MMSE equalizer and a partial MMSE-OSIC equalizer appropriately, according to symbol selection algorithm. This algorithm chooses the number of selected symbols which should be detected by the OSIC scheme based on the required reliability (RR) of each subchannel. The RR of each subchannel means the target signal-to-interference plus noise ratio (SINR) of symbol in each subchannel. Furthermore, to reduce the computational complexity in the partial MMSE-OSIC, the average number of selected symbols is maintained under the threshold value appropriately in low SNR. It is shown in simulation results that the performance of the proposed equalizer is close to that of the existing MMSE-OSIC equalizers with high computational complexity (ges O(N2)), while achieving a significant reduction in computational complexity (O(N)).

In this letter, a novel time-domain recursive algorithm is proposed for a minimum-mean-squared error (MMSE) with successive interference cancellation (SIC) scheme. This algorithm allows us to reduce the complexity of classical MMSE-SIC equalizer for suppressing intercarrier interference (ICI) caused by time-varying multipath channels in orthogonal frequency division multiplexing (OFDM) systems, and it can provide almost the same performance as that of the optimal MMSE-SIC equalizer. It is shown in complexity analysis that the proposed scheme shows better complexity reduction than previously reported low-complexity MMSE-SIC schemes when applied to a channel equalizer for an OFDM system.