Long delay multipath is a major cause of the poor reception of digital terrestrial broadcasting signals. The direct solution to this problem in orthogonal frequency division multiplexing (OFDM) system is to make the guard interval (GI) longer than the maximum channel delay. However, given the wide variety in broadcasting channel characteristics, the worst case GI may be twice the value needed which decreases the spectral efficiency and service quality. Therefore, the solution must be implemented on the receiver side. For the next generation broadcasting system, this paper proposes a space division multiplexing (SDM) multiple-input multiple-output (MIMO)-OFDM receiver for a multipath environment whose maximum delay time exceeds the GI length. The proposed system employs the high frequency resolution spatial filters that have the same configuration as the conventional one but operate at four times higher frequency resolution. Computer simulation and laboratory test results are presented to show the effectiveness of the proposed system.

In this letter, a switching detection scheme based on a channel condition number for the MIMO-OFDM system is proposed. The switching algorithm operates by selecting one of three detection schemes of QRD-M, LR-aided MMSE-DFE, and LR-aided MMSE. The switching detection uses the threshold based on the switching algorithm according to the channel condition number. From the simulation results, the proposed detection scheme shows error detection performance and computational complexity in accordance with the threshold for switching detection.

The Long Term Evolution (LTE) of mobile communication standard was designed by the 3rd generation partnership project (3GPP) to serve the requirements. Nowadays, the combining of the orthogonal frequency division multiplexing (OFDM) and the multiple input multiple output (MIMO) is supported in LTE system. The MIMO-OFDM is considered to improve data rate and channel capacity without additional bandwidth. Because the receivers get all transmission signals from all transmitters at the same time, many detection schemes have been developed for accurate estimation and low complexity. Among the detection schemes, the QR decomposition with M algorithm (QRD-M) achieves optimal error performance with low complexity. Nevertheless, the conventional QRD-M has high complexity for implementation. To overcome the problem, this letter proposes the low complexity QRD-M detection scheme in MIMO-OFDM systems. The proposed scheme has two elements which decide layer value and the limited candidates. The two elements are defined by the number of transmit antennas and the cardinality of modulation set respectively. From simulation results, the proposed scheme has the same error performance with the conventional QRD-M and very lower complexity than the conventional QRD-M.

We propose a pre-filtering system for blind equalization in order to separate orthogonal frequency division multiplexing (OFDM) symbols in a multiple-input multiple-output (MIMO) - OFDM system. In a conventional blind MIMO-OFDM equalization without the pre-filtering system, there is a possibility that originally transmitted streams are permutated, resulting in the receiver being unable to retrieve desired signals. We also note that signal permutation is different for each subcarrier. In order to solve this problem, each transmitted stream of the proposed MIMO-OFDM system is pre-filtered by a unique allpass filter. In this paper, the pre-filter is referred to as transmit tagging filter (TT-Filter). At a receiver, an inverse filter of the TT-filter is used to blindly equalize a MIMO channel without permutation problem. Further, in order to overcome the issue of phase ambiguity, this paper introduces blind phase compensation.

This letter proposes a situation-adaptive detection algorithm for the improved efficiency of the detection performance and complexity in the MIMO-OFDM system. The proposed algorithm adaptively uses the QRD-M, DFE, and iterative detection scheme in according to the detection environment. Especially, the proposed algorithm effectively reduces the occurrence probability of error in the successive interference cancellation procedure by the unit of the spatial stream. The simulations demonstrate that the adaptive detection method using the proposed algorithm provides a better trade-off between detection performance and complexity in the MIMO-OFDM system.

Recently, among MIMO-OFDM detection schemes, a lot of V-BLAST schemes have been suggested in order to achieve high data rate. Therefore signal detection of MIMO-OFDM system is important issue. In this letter, extended DFE detection scheme is proposed. According to simulation result, the extended DFE detection has similar performance with QRD-M detection but the complexity is about 24.02% of QRD-M detection. Therefore the proposed E-DFE detection can be efficiently used in MIMO-OFDM system.

In this letter, an enhanced detection scheme using threshold and lattice-reduction algorithm is proposed. The first step of the proposed detection scheme finds another basis channel matrix H' which has good properties from the channel matrix H by using lattice-reduction algorithm. And QRD-M detection scheme using threshold algorithm is executed in the next step. Simulation results show that the proposed method has better performance than the conventional QRD-M detection scheme at high SNR. Also, it reduces candidate symbols because of the threshold algorithm.

In this letter, a robust time synchronization algorithm is proposed for MIMO-OFDM based WLAN systems. IEEE 802.11ac MIMO-OFDM WLAN standard specifies that the preamble with cyclic shift diversity (CSD) scheme is used for time and frequency synchronization. However, since the CSD scheme introduces multiple cross-correlation peaks at the receiver, serious performance degradation appears if the conventional cross-correlation based algorithm is applied. In the proposed algorithm, the time synchronization error due to multiple peaks is compensated by adding the cross-correlation value to its reverse cyclic-shifted version. Simulation results show that the proposed algorithm achieves an SNR gain of 1.5 to 4.5dB for the synchronization failure rate of 10-2 compared with the existing algorithms.

Joint signal detection and channel estimation based on the expectation-maximization (EM) algorithm has been investigated for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) mobile communications over fast-fading channels. The previous work in [20] developed a channel estimation method suitable for the EM-based iterative receiver. However, it remained possible for unreliable received signals to be repetitively used during the iterative process. In order to improve the EM-based iterative receiver further, this paper proposes spatial removal from the perspective of a message-passing algorithm on factor graphs. The spatial removal performs the channel estimation of a targeted antenna by using detected signals that are obtained from the received signals of all antennas other than the targeted antenna. It can avoid the repetitive use of unreliable received signals for consecutive signal detection and channel estimation. Appropriate applications of the spatial removal are also discussed to exploit both the removal effect and the spatial diversity. Computer simulations under fast-fading conditions demonstrate that the appropriate applications of the spatial removal can improve the packet error rate (PER) of the EM-based receiver thanks to both the removal effect and the spatial diversity.

In this letter, an improved channel-adaptive detection scheme based on condition number combined with a QRD-M and CLLL algorithms is presented for MIMO-OFDM systems. The proposed scheme estimates the channel state by using the condition number and then the number of layers for the QRD-M is changed according to the condition number of channel. After the number of layers is determined, the proposed scheme performs the combined QRD-M and CLLL. Simulation results show that the BER curves of the proposed scheme and QRD-M using CLLL have similar performance. However, the complexity of the proposed scheme is about 27% less than QRD-M detection using CLLL.

This paper describes a simple packet combining scheme with maximum likelihood detection (MLD) for multiple-input multiple-output with orthogonal frequency division multiplexing (MIMO-OFDM) in relay channels to construct reliable wireless links in wireless local area networks (LANs). Our MLD-based approach employs the multiplexed sub-stream signals in different transmit slots. The proposed scheme uses an additional combining process before MLD processing. Moreover, the proposed scheme sets the cyclic shift delay (CSD) operation in the relay terminal. We evaluate the performance of the proposed scheme by the packet error rate (PER) and throughput performance in the decode-and-forward (DF) strategy. First, we show that the proposed scheme offers approximately 4.5dB improvement over the conventional scheme in the received power ratio of the relay terminal to the destination terminal at PER =0.1. Second, the proposed scheme achieves about 1.6 times the throughput of the conventional scheme when the received power ratio of the relay terminal to the destination terminal is 3dB.

Although the QR decomposition M algorithm (QRD-M) detection reduces the complexity and achieves near-optimal detection performance, its complexity is still very high. In the proposed scheme, the received symbols through bad channel conditions are arranged in reverse order due to the performance of a system depending on the detection capability of the first layer. Simulation results show that the proposed scheme provides almost the same performance as the QRD-M. Moreover, the complexity is about 33.6% of the QRD-M for a bit error rate (BER) with 4×4 multi input multi output (MIMO) system.

In this letter, advanced QRD-M detection using iterative scheme is proposed. This scheme has a higher diversity degree than conventional QRD-M detection. According to the simulation results, the performance of proposed QRD-M detection is 0.5dB to 5.5dB better than the performance of conventional QRD-M detection and average iteration time is approximately 1 in the value of M = 1, 2, 3. Therefore, the proposed QRD-M detection has better performance than conventional QRD-M detection, particularly in a high SNR environment and low modulation order.

A joint superimposed sequence design, known as SuperImposed sequence for PAPR Reduction, or SIPR, using per-tone affine precoding technique is proposed to jointly estimate MIMO-OFDM channels and reduce the peak-to-average power ratio (PAPR) for MIMO-OFDM systems. The proposed technique optimizes the trade-off between BER, MSE of the channel estimate, and PAPR reduction performance. Moreover, it does not require side information to be transmitted for the removal of the sequence at the receiver, and the transmit redundancy can be as small as 1 symbol/subcarrier. The superimposed sequence is designed by solving a convex quadratically constrained quadratic programming problem and has a computational complexity comparable to previous technique using linear programming. It is shown that SIPR can be regarded as a generalization of the popular tone reservation (TR) technique, and thus, is able to outperform TR in terms PAPR reduction performance, with less transmit overhead. Simulation results and transmit redundancy analysis of SIPR and TR are shown to illustrate the efficacy of the proposed scheme.

In this letter, an adaptive detection scheme for a multiple-input multiple-output (MIMO) system is proposed. In order to reduce the complexity of the decoding steps, the initial symbol is obtained by a MMSE equalizer and then the symbol ordering is performed by the channel state. After the received symbols are divided according to the channel state, some of the symbols are detected by using the MMSE detector with low complexity. With cancelation processing, the remainder symbols are detected for the K-best detector. The proposed adaptive detection scheme combines the MMSE and K-best detector based on the channel state. Therefore, the proposed adaptive detector achieves a good performance.

In this letter, a novel adaptive detector that combines DFE and QRD-M is proposed for MIMO-OFDM system. QR decomposition (QRD) is commonly used in many MIMO detection algorithms. In particular, sorted QR decomposition (SQRD) is an advanced algorithm that improves MIMO detection performance. The proposed detector uses SQRD to achieve better performance. To reduce the computational complexity, the received layers of each subcarrier are ordered by using the post SNR and are detected by DFE and QRD-M detector based on the order. Therefore, the proposed detector structure is varied according to the channel state. In other words, the proposed detector achieves a good tradeoff between complexity and performance. A simulation confirms the substantial performance improvements of the proposed adaptive detector with only slightly greater complexity than the conventional detector.

In this paper, a modified detection approach based on minimum mean-square error (MMSE) sorted QR decomposition (SQRD) for turbo coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is presented. In conventional MMSE SQRD based detection, a component of the symbol to be detected is still present in the interference term, leading to less efficient log likelihood ratios (LLRs) passed to soft decoder. By moving this symbol component into the signal term, the modified MMSE SQRD based detection can provide more efficient LLRs for soft decoder. Simulation results show that the proposed detection can achieve significant performance gain.

In this letter, we propose a innovative threshold receiver for MIMO-OFDM system. The proposed scheme calculates the channel condition number and then selects either combined V algorithm and CLLL or combined QRD-M and DFE detection scheme according to channel information. The complexity of the proposed scheme is about 33.3% of the QRD-M for 44 MIMO-OFDM system.

MIMO-OFDM combining OFDM and MIMO techniques achieves high spectral efficiency and is able to increase throughput. MIMO-OFDM systems can be classified into either “open loop” or “closed loop” depending on whether the CSI is fed back from the Rx to the Tx. As a closed loop scheme, SVD-MIMO is the optimal single user MIMO-OFDM transmission scheme while it requires knowledge of the CSI at both the Tx and Rx. In practical systems, Tx weight is fed back from the Rx to the Tx by limited bits and with feedback delay, which causes mismatch between the weight and the real channel especially if the channel exhibits time variation. Hence, the transmission performance of the SVD-MIMO scheme degrades. Therefore, the performance comparison between open loop and closed loop schemes against channel variation is very important for practical deployment of MIMO-OFDM systems. For that purpose, a unified performance calculation method for the open loop and the closed loop MIMO-OFDM schemes with finite and delayed feedback is developed in this paper. The method is effective for analysis of both STBC for the open loop and SVD-MIMO using codebook for the closed loop with per stream layer AMC. Also, to combat frequency selective fading in practical wireless channels, an interleaver is employed in this paper. In numerical analyses, it is found that simulation results agree well with the derived theoretical performance results. Secondly, from these results, the cross-over point of the throughput performance of two schemes in terms of UE velocity and SNR is found.

The multiple-input multiple-output (MIMO)-Orthogonal frequency division multiplexing (OFDM) system has a serious drawback in that it has high peak-to-average power ratio (PAPR). Therefore, in this letter, we propose an effective PAPR reduction scheme for MIMO-OFDM systems with nonlinear high power amplifier (HPA). The proposed scheme very effectively reduces the PAPR through the adaptive nonlinear estimator (ANE) which estimates the MSE between the OFDM signals before and after the nonlinear HPA and the low probability of false side information (SI) by receive diversity.