Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing Systems Research Articles

The Effectiveness of LDPC Decoding Algorithms in 5G Channel Modelling of MIMO-OFDM System under the Influence of Spatial Correlation

This paper investigates the spatial cross-correlation properties of 5G channel modeling in non-line of sight (NLOS) of Urban Micro Cell (UMi), Rural Macro Cell (RMa) and Indoor Cell (InH) at 6 GHz frequency band as Third Generation Partnership Project (3GPP) specification. In our spatial correlation Multiple-input multiple-output (MIMO) channel, when increasing the distances of BS antenna elements, the correlation characteristics of the channel dramatically vary, which leads to altering the observed system behavior. By analyzing the 5G LDPC code and using different decoding algorithms and code rates, we evaluate the system’s performance by Bit Error Rate (BER) in a wideband correlated Multiple-input multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. In our spatial correlation, the more rising of the distances of antenna elements on the BS side, the better the effectiveness of the LDPC decoding algorithms achieved. Of the Belief Propagation based (BP-based) Algorithm, Offset Minimum-Sum (OMS) Algorithm and Linear Approximation Minimum-Sum (LAMS) Algorithm, we propose to use the LAMS decoding algorithm with a high code rate of 5/6 in our spatial correlated wideband channel because of lower complexity and more efficiency in term of the system’s performance.

Comparison on BER Performance Using Linear Filtering Least Square Method and Least Square Method for MIMO-OFDM Based Communication Systems

In Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the Bit Error Rate is poor by using Linear Filtering Least Square method (LFLS) and Least Square (LS) method for massive MIMO-OFDM systems to extend the strength of the signal and to scale back the noise. Therefore the objective of the project is to maintain better Bit Error Rate performance. Materials and methods: Using Linear Filtering Least Square method, different values are used to enhance the Bit Error Rate (BER). The proposed method is compared with the least square method, the results are obtained by using Matlab simulation software. Results: The performance of Bit Error Rate is calculated by using the Linear Filtering Least Square method and enhanced Least Square method parameters. At 20 dB SNR, the linear filtering least-square provides the BER value is 10-3, whereas the Novel enhanced least-square scheme provides the BER value around 10-5. Conclusion: Based on experimental results and statistical analysis using the independent sample T-test, the Least Square method significantly performs better than the Linear Filtering Least Square method.

A Novel Non-Hermitian Symmetry Orthogonal Frequency Division Multiplexing System for Visible Light Communications

This paper proposes a novel non-Hermitian symmetry ${2 \times 2}$ MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) system based on fast Hartley transform (FHT) with unipolar encoding (referred to as HU-OFDM) for visible light communications. The new scheme uses FHT instead of FFT (fast Fourier transform) to process the complex-valued signals reducing the computational complexity and hardware cost and employs two LEDs (light-emitting diodes) to transmit the real and imaginary parts of a complex-valued OFDM signal respectively. Unipolar encoding is applied to the transmitted signal from each LED to ensure non-negative. The restrictions of Hermitian symmetry in traditional optical OFDM systems and real constellation mapping in FHT based optical OFDM systems can be removed simultaneously in the proposed system. Compared with MIMO-ACO/DCO-OFDM system, HU-OFDM has significant performance improvement along with a tremendous decrease in hardware cost and computational complexity. Compared with other non-Hermitian symmetry MIMO-OFDM systems, HU-OFDM has significant advantages in terms of power efficiency, system design flexibility, computational complexity, or hardware cost without losing reliability.

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems.

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.

Space-Frequency Coded Quadrature Index Modulation With Linear Maximum Likelihood Detection

This paper focuses on the issue of achieving transmit diversity for the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system working with quadrature index modulation (QIM). Inspired by the ideas of quadrature spatial modulation (QSM) and quadrature space-frequency index modulation (QSF-IM), parts of the space-frequency resource units in each resource block (RB) of the MIMO-OFDM system are activated twice independently to send the in-phase and quadrature components of a space-frequency code, respectively, to achieve the second order transmit diversity. Thus the proposed scheme is called space-frequency coded QIM (SFC-QIM). The SFC-QIM scheme allows for a linear-complexity maximum likelihood (ML) receiver, which benefits from the orthogonality between the real and imaginary parts of the symbols in the SFC codewords. Owing to obtaining higher diversity order, simulation results of bit error rate (BER) performance demonstrate that the new SFC-QIM scheme outperforms some existing IM schemes in both independent and identically distributed (i.i.d.) and correlated Rayleigh fading channels.

Multilevel Redundant Discrete Wavelet Transform (ML-RDWT) and Optimal Red Deer Algorithm (ORDA) Centred Approach to Mitigate the Effect of ICI, BER and CIR in a MIMO-OFDM System

Nowadays, there is a great demand for ultra-high data rate (UHDR) transmission on most 5th generation wireless networks. In this concern, the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) scheme is used on a large scale to achieve UHDR transmission with reduced inter-symbol interference (ISI) and inter-carrier interference (ICI). Discrete wavelet transform-based OFDM (DWT-OFDM) provides better orthogonality due to presence of orthogonal wavelets, which mitigates the effects caused by ISI and ICI. Also, it has extended bandwidth than the traditional OFDM systems. But a major drawback in this system is that it suffers from down sampling. The down-sampling effect reduces the actual size of the input bit streams. As a result, the system performance is degraded. For solving this problem, a multilevel redundant discrete wavelet transform (ML-RDWT) is used instead of DWT to achieve improved spectral performance. Here, complex down-sampling operation is eliminated. From the simulation outcomes, it is clearly viewed that effects caused by ICI, ISI and BER are mitigated by improving the performance of CIR. The proposed method employs optimal red deer algorithm (ORDA) to locate the optimized weights for the ICI cancellation system. This algorithm enhances the spectral efficiency by achieving high CIR with reduced BER, ISI and ICI. The BER in the proposed MIMO-ML-RDWT-OFDM-ORDA method is 68%, 76%, 38% and 75%, which is very low when compared to the BER in the existing techniques like MIMO-DWT-OFDM-RDA, MIMO-RNS-OFDM-PNMA, MIMO-OFDM-BMA and MIMO-OFDM-ICIMA. The ISI in the proposed method is 94%, 91%, 95% low when compared to the ISI in the existing techniques. The ICI in the proposed work is 71%, 57%, 73% and 86% low when compared to the ICI in the existing techniques. Therefore, the general performance of the proposed MIMO-ML-RDWT-OFDM-ORDA method is improved in an efficient way with less complexity, error rate and processing delay.

A PROFICIENT PILOT DESIGNING PATTERN FOR CHANNEL ESTIMATION IN MIMO-OFDM SYSTEMS

The high data transmission rates in the communication channel is a recent growing demand which is achieved by using the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems because of their unique properties.. The OFDM systems that adopt the cyclic-delay diversity (CDD) scheme require only one inverse discrete Fourier transform (IDFT) operation at the transmitter. Hence, the CDD provides a low-complexity by means of increasing the transmission diversity in MIMO-OFDM systems. However, the optimal pilot sequences which minimize the mean square error (MSE) of the channel estimate in traditional MIMO-OFDM systems are inapplicable to CDD-OFDM systems. Thus this paper originates by deriving the criteria which yield the minimum MSE of both the least square (LS) channel estimate and the MMSE channel estimate in CDD-OFDM systems. The derived criteria are then used to develop a general methodology for determining the optimal pilot sequence. Significantly, the proposed design methodology enables the status of the channel to be estimated using single OFDM symbol. We have compared the performances of channel estimation algorithm by measuring bit error rate vs. SNR with BPSK, QPSK 16-PSK and 256-PSK modulation schemes.

Experimental Evaluation of Machine learning based MIMO-OFDM System for Optimal PAPR and BER

The hypothetically convenient structure is the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) technique that is employed for upcoming generations in wireless communication systems. Some of the benefits offered by MIMO-OFDM are enhanced spatial multiplexing, reliability and network throughput, and so on. Due to the integration of spatial antenna that is based on multi-stream, the problems which are related to significantly high power takes place in the system of OFDM and provides complex processing strategies. Some of the popularly known systems that are used for standardizing the Peak to average power ratio (PAPR) are partial transmit sequences (PTS), adoptive tone reservation (ATR), probabilistic mapping, and clipping which are required to be truncated and aims for minimizing the operational cost. The framework of hybrid Selective Mapping (SLM)-PTS proposed in this paper minimizes the operational cost by integrating strategies of PTS and SLM. A reduction approach that is suitable for PAPR and BER are chosen for optimization purposes depending on the statistical threshold constraint of PAPR and Bit Error Rate (BER). Thus, the system preferred with the help of the machine learning technique demonstrates the efficiency in implementing a generalized strategy to evaluate a low complexity MIMO-OFDM model. Ultimately, with the help of the PAPR and BER techniques-driven from value bound the performance of the error rate is evaluated in this framework that interactively changes from one technique.

A criterion based adaptive RSIC scheme in underwater communication

Multi-access interference (MAI) is the main source limiting the capacity and quality of the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Therefore, multi-user detection (MUD) is needed at the receiver of the MIMO-OFDM system to suppress the effect of MAI. In this research, MUD is achieved by using a criterion based adaptive recursive successive interference cancellation (RSIC) scheme at the receiver of a MIMO-OFDM system whose transceiver model in underwater communication is implemented by using the Bellhop simulation system. The proposed scheme estimates and eliminates the MAI through user signal detection and subtraction from received signals at the receiver of the MIMO-OFDM system in underwater environment. The bit error rate (BER) performance of the proposed scheme is analyzed by using weight filtering and weight selection criteria. By Matlab simulation, it is shown that the BER performance of the proposed scheme outperforms the conventional matched filter(MF) detector, the adaptive successive interference cancellation(SIC) scheme, and the adaptive RSIC scheme in the UWA network.

Multiuser Detection for MIMO-OFDM system in Underwater Communication Using a Hybrid Bionic Binary Spotted Hyena Optimizer

Multi Access Interference (MAI) is the main source limiting the capacity and quality of the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Multi User Detection (MUD) is needed to overcome the performance degradation caused by MAI. In this research, both local and global optimal solutions are obtained in Bionic Binary Spotted Hyena Optimizer (BBSHO) algorithm using the Position Coordinate Vectors (PCVs) of the social behavior of spotted hyenas to achieve MUD. Further, Extremal Optimization (EO) is introduced in BBSHO algorithm to improve the local search ability within the search space. Hence, a hybrid BBSHO algorithm is proposed for achieving MUD at the receiver of the MIMO-OFDM system whose transceiver model in underwater is implemented using BELLHOP simulation system. By MATLAB simulation, it is shown that the Bit Error Rate (BER) performance of the proposed hybrid algorithm outperforms with best optimal solution within the search space towards MUD for Interference to Noise Ratio (INR) at 10 dB, 20 dB, and 40 dB over conventional detectors and metaheuristic approaches such as Binary Spotted Hyena Optimizer (BSHO), Binary Particle Swarm Optimization (BPSO) in the UWA network.

Relay Selection Scheme Enhancing Reliability Based on MIMO-OFDM System

In this paper, a relay selection scheme is proposed in the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. The conventional relay selection schemes in the wireless cooperative communication system have high implementation complexity and overhead. The proposed scheme is an adaptive relay selection scheme using Singular Value Decomposition (SVD) to select a relay with channel coefficients that maximize channel capacity. Proposed scheme uses combining factor with singular value in order to combine received signal. Simulation result shows that the proposed scheme improves the Bit Error Rate (BER) performance, compared with the conventional schemes. The proposed scheme with combining factors has enhanced BER performance than the conventional schemes.

Analysis of LSE and MMSE Pilot Based Channel EstimationTechniques for MIMO-OFDM System

An Orthogonal Frequency Division Multiplexing(OFDM) has becoming a desirable modulation technique scheme for wireless systems. In recent years, with the advent of technology in Very Large-Scale Integration (VLSI), the number of higher data level is growing. Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems are used to meet these criteria due to their high performance, in terms of transmission range, data rate resistance to multi-path transmission. A MIMO OFDM framework is designed for systems such as IEEE 802.11n, 4 G and LTE in advanced communication systems. It provides secure transmission with a growing coverage area. The estimation of Channel State Information (CSI) is the biggest challenge in the implementation of MIMO-OFDM method. We evaluate and enforce the pilot-based channel analysis methods for MIMO-OFDM system such as Minimum Mean Square Errors (MMSE), Least Square (LS).

Maximum likelihood-based adaptive iteration algorithm design for joint CFO and channel estimation in MIMO-OFDM systems

In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.

PAPR reduction of MIMO-OFDM using galaxy inspired swarm-based PTS strategy

Multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is a striking scheme, which has procured noteworthy importance as an auspicious contender for not only 4th generation but 5th generation wireless communication also. However, the mountainous problem regarding MIMO-OFDM is its considerably high peak to average power ratio (PAPR). In this literature, partial transmit sequence (PTS) mechanism is instigated on MIMO-OFDM system. Its effectiveness verification is displayed with assorted simulation results. Results reveals that PTS strategy not only refine but boost the potential of the MIMO-OFDM-based system, moreover, it has hitherto been indicated that with rise in sub-blocks, that are mostly non-overlapping, PAPR performance enhances. Further, the phase factors of MIMO-OFDM-based system are optimised by evolutionary techniques which drives its inspiration from galaxies called galaxy inspired swarm-based optimisation (GSO).

BER Assessment of OFDM System Augmented with MRC Technique under the Effect of CFO

Orthogonal frequency division multiplexing (OFDM) and Multiple input multiple output (MIMO) is capable to enhance data rates over the radio channel providing enough protection against the destructions caused in the path of the signal. But the bit error rate (BER) of the systems degrades due to the presence of Carrier frequency offset (CFO). The presence of CFO results in generation of Inter Carrier Interference (ICI) which in turn results in loss of orthogonality between the sub carriers. The significance of MIMO-OFDM is due to orthogonality among the carriers which is at stake due to presence of CFO. In this paper, the performance of the MIMO–OFDM system is analyzed over the Rayleigh channel for 2 and 3-array antennas under the effect of CFO with Maximal Ratio Combining (MRC) diversity technique at receiver section. It is observed from simulations that the MIMO-MRC reduces the BER and improves the overall performance of the system which is very much useful to combat against the effects of CFO.

A New Efficient Two-Sided Complementary Code Based Channel Estimation Technique “TSCC-CE” for MIMO-OFDM Systems, Under the Effects of Partial-Band Jamming and Doppler Spread

Channel estimation (CE) is a field of study that has garnered much attention during recent years. CE plays an important role in developing channel equalizers. There are many approaches to CE, among which there are orthogonal codes (OC) and orthogonal space-time block codes (OSTBC). Also, complementary codes (CC) have been under investigation for multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) CE. There are zero side-lobe levels in a CC signal’s autocorrelation function. The initial area of application of these signals has been radar systems, and they were used as optimal phase-coding signals. These signals require the use of two different channels to transmit the twofold components of the pilot code. Thus, this research introduces the two-sided CE (TSCE), where separate subcarrier locations are used to carry the two pilot CCs. Equalization errors can occur in dangerous situations, in case a system is interfered with or jammed. This leads to negative impacts on the accuracy of channel estimation. This situation specifically occurs when a harsh Doppler spread is present, as a result of a deterioration in the orthogonality of the subcarriers of the OFDM. Certain conditions were applied for testing the performance of the method suggested in this paper, i.e., the MIMO-OFDM TSCE approach, the method that depends on CCs. These conditions are the Doppler spread, as well as partial-band jamming. Among the different MIMO-OFDM CE techniques, TSCC-CE has shown good performance, with its ability to withstand the effect of partial-band jamming on the accuracy of the MIMO-OFDM CE. This improved performance takes place in the presence of a Doppler spread of moderate value and a partial-band jamming ratio.

Broad Echo State Network for Channel Prediction in MIMO-OFDM Systems

Channel prediction is a vital technique that can be used to support adaptive transmissions and mitigate the feedback delay of the channel state information (CSI) in the wireless communications, especially in the frequency division duplex (FDD) system. In this paper, we focus on the channel prediction issue in multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. First, we introduce the general channel prediction framework based on the temporal and spatial correlations in MIMO-OFDM systems. Then, we combine the broad learning idea and recurrent computation, and further introduce the broad echo state network (BESN) for channel prediction in MIMO-OFDM systems. Third, to estimate the output weight matrix, we offer two versions of the BESN, i.e., the basic BESN (B-BESN) and the group forward variable selection (GFVS)-based BESN (GFVS-BESN). In the latter, we develop the GFVS strategy to further extract useful information from those collected features in the BESN and make the BESN more able to process the CSI samples. Fourth, inspired by deep learning, we import the conjugate gradient descent backpropagation (CGDBP) technique to fine-tune the random weights and biases in the BESN and give the related derivations. Then, we prove the echo state property in the BESN and analyze the computational complexity. In the simulation section, we comprehensively evaluate the prediction performances for the standard Extended Vehicular A model (EVA) and Extended Typical Urban model (ETU) under different signal-to-noise ratios (SNRs), different antenna configurations, different spatial correlations, different maximum Doppler shifts and different channel prediction methods. The simulation results indicate that the BESN has excellent prediction performance in MIMO-OFDM systems.

Compensation of Non-linear Distortion Effects in MIMO-OFDM Systems Using Constant Envelope OFDM for 5G Applications

Orthogonal frequency division multiplexing (OFDM) is a multicarrier transmission system that can achieve high data rate over wireless channels. At the same time, multiple input multiple output OFDM (MIMO-OFDM) in wireless communication systems has been exposed to offer significant improvement over wireless technology by providing transmit diversity. It has become a promising technique for high-performance 5G broadband wireless communications. However, the main problem associated with MIMO-OFDM is that its signal exhibits high peak-to-average power ratio (PAPR), which causes nonlinear distortion and consequently performance degradation. Besides, PAPR carries weaknesses such as an increase in power consumption of high power amplifier (HPA) and analog to digital converter (ADC). Thus, 5G base stations will push up power requirements because energy consumption grows with the number of transceiver elements. So, mobile operators must find the right compromise that, on the one hand, guarantees a certain level of performance to a data flow, and, on the other hand, the energy cost generated for the deployment of the network. For this, as part of the management of power consumption, we propose MIMO constant envelope OFDM (MIMO-CE-OFDM) technique. In this work, we used MIMO-CE-OFDM to mitigate the nonlinear effect of HPA and ADC. To perform practical simulations, we have used COST 2100 MIMO channel model. In this paper, a MIMO-CE-OFDM system has been presented and analyzed under COST 2100 channel model conditions. Simulation results are given to illustrate the performance of [Formula: see text] MIMO-CE-OFDM in the presence of both HPA and ADC nonlinearity. This work shows that the effect of nonlinearity is shown to be negligible on MIMO-CE-OFDM signal.

A Downlink Multiuser MIMO–OFDM System With Nonideal Oscillators and Amplifiers: Characterization and Performance Analysis

In this article, we analytically investigate the performance of a downlink multiuser (MU) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with hardware impairments. Specifically, we focus on the joint impact of nonideal oscillators and nonlinear high-power amplifiers, which can be quantified in terms of multiplicative and additive nonlinear distortions as well as phase noise, which causes inter-channel interference (ICI). We first derive the signal-to-distortion-plus-interference-plus-noise ratio (SDINR) and then utilize the SDINR to derive the closed-form expressions for symbol-error-rate and the average capacity of the aforementioned system. Our analysis shows that the statistics of an additive nonlinear distortion and additive white Gaussian noise are not affected by phase noise. However, the phase noise itself significantly deteriorates the performance of the MU-MIMO-OFDM system even in the absence of the nonlinear distortions. We further show that nonlinear distortion and ICI cause an irreducible error floor which considerably degrades the system error performance and also adversely affects the total capacity of the MU-MIMO-OFDM system. Comparisons are drawn between the performance of an ideal MU-MIMO-OFDM system and a MU-MIMO-OFDM system in presence of above impairments. In the end, we present the simulation results to validate the efficacy of our theoretical analysis.

Optimal IA design and performance analysis for MIMO–OFDM systems with imperfect CSI

Both multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are key technologies for the fifth-generation mobile communication systems. However, interference is one of the critical challenges in MIMO–OFDM systems that degrades the overall performance. In this study, a novel interference alignment (IA) design-based diagonal-block channel charter to mitigate the interference for MIMO–OFDM systems is proposed. The proposed IA scheme can be used in physical layer security, e.g. anti-location. Based on the diagonal-block charter of the channel matrix, the optimal degree of freedom, i.e. the maximum number of multiple data streams concurrently transmitted interference-free can be achieved by IA. Correspondingly, the authors present the closed-form IA design scheme for some special scenarios, and two iterative IA ones for general scenarios in detail. Furthermore, the performance analysis of IA systems with diagonal-block channel error is provided, where the imperfect channel state information case is considered. The simulation results show that the IA design based on the diagonal-block channel can improve the sum-rate performance effectively, by sufficiently exploiting the spatial and frequency resources.