Differential Spatial Modulation Mapping Algorithms

Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio frequency chain.In this paper,DSM is investigated using two mapping algorithms:Look-Up Table Order(LUTO)and Permutation Method(PM).Then,the bit error rate(BER)performance and complexity of the two mapping algorithms in various antennas and modulation methods are verified by simulation experiments.The results show that PM has a lower BER than the LUTO mapping algorithm,and the latter has lower complexity than the former.

Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

Switching between multiplexing and diversity in MIMO systems with QoS provisioning

Multiple-input multiple-output (MIMO) wireless communication systems can significantly improve the spectrum efficiency or transmission reliability through spatial multiplexing or diversity respectively.Most of previous works mainly have focused on the multiplexing-diversity tradeoff or switching between multiplexing and diversity without considering the property of heterogeneous QoS provisioning.In this paper,switching between multiplexing and diversity in MIMO system with the heterogeneous QoS provisioning is studied.Firstly the QoS provisioning for users are classified into two classes:users with real time service requirement and users with non-real time service requirement respectively.Then based on the heterogeneous QoS Provisioning for users,two different switching criterions are proposed,switching based on the Euclidean distance for users with real time service to minimize the probability of symbol error and capacity-based switching criterion for users with non-real time service to maximize the transmission capacity respectively.Finally,numerical simulation results are illustrated to demonstrate the performance of proposed scheme.

Limited feedback SDMA schemes based on statistical CSI

This paper investigates the multi-beam selection algorithms for transmit correlation channels by using statistical channel state information （SCSI） and instantaneous channel state information. Unlike the conventional codebook-based transmission scheme, the proposed multi-beam selection with the single channel quality indicator （CQI） feedback （MBS- SCF） algorithm determines the preferred beam vector by exploiting the SCSI and only feeds back CQI at each timeslot. The performance of the MBS-SCF algorithm is nearly the same as that of the conventional scheme. In order to further improve the average sum rate, a novel multi-beam selection with the dual CQIs feedback （MBS-DCF） algorithm is proposed, which determines dual preferred statistical eigen- directions and feeds back dual CQIs at each timeslot. The theoretical analysis and simulation results demonstrate that the MBS-DCF algorithm can increase the multiuser diversity and multiplexing gain and exhibits a higher average sum rate.

Dynamic resource allocation for high-speed railway downlink MIMO-OFDM system

The dynamic resource allocation problem in high-speed railway downlink orthogonal frequency-division multiplexing（OFDM） systems with multiple-input multiple-output（MIMO） antennas is investigated.Sub-carriers,antennas,time slots,and power are jointly considered.The problem of multi-dimensional resource allocation is formulated as a mixed-integer nonlinear programming problem.The effect of the moving speed on Doppler shift is analyzed to calculate the inter-carrier interference power.The optimization objective is to maximize the system throughput under the constraint of a total transmitted power that is no greater than a certain threshold.In order to reduce the computational complexity,a suboptimal solution to the optimization problem is obtained by a two-step method.First,sub-carriers,antennas,and time slots are assigned to users under the assumption of equal power allocation.Next,the power allocation problem is solved according to the result of the first-step resource allocation.Simulation results show that the proposed multi-dimensional resource allocation strategy has a significant performance improvement in terms of system throughput compared with the existing one.

Joint timing synchronization and frequency offset acquisition algorithm for MIMO OFDM systems

For multiple-input multiple-output （MIMO） orthogonal frequency division multiplexing （OFDM） systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform （FRFT） is proposed. The linear frequency modulation signals superimposed on the data signals are used as the training signals. By performing FRFT on the received signals and searching the peak value of the FRFT results, the receiver can realize timing synchronization and frequency offset acquisition simultaneously. Compared with the existing methods, the proposed algorithm can provide better timing synchronization performance and larger frequency offset acquisition range even under multi-path channels with low signal to noise ratio. Theoretical analysis and simulation results prove this point.

Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems

A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based （EKF-based） channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square （LS） and the least mean square （LMS） methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer draznatic system performance improvement at a modest cost of computational complexity.

Fast multi-parameter estimation and localization for MIMO radar

This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.

Impact of Depolarization Phenomena on Polarized MIMO Channel Performances

The performance and capacity of multiple-input multiple-output (MIMO) wireless channels are limited by the spatial fading correlation between antenna elements. This limitation is due to the use of mono polarized antennas at receiver and transmitter sides. In this paper, in order to reduce the antenna correlation, the polarization diversity technique is employed. Although the spatial antenna correlation is attenuated for multi-polarization configurations, the cross-polar components appear. This paper highlights the impact of depolarization effect on the MIMO channel capacity for a 4×4 uniform linear antenna array. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is distributed to each of the transmit antennas. The numerical results illustrate that for low depolarization and spatial correlation, the capacity of single-polarization configuration behaves better than that of multi-polarization configuration.

Sparse channel estimation for MIMO-OFDM systems using distributed compressed sensing

A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.

Precoding for Multiuser Spatial Multiplexing MIMO Downlink

Previous precoding algorithms have concentrated on the single user scenario where the precoding scheme assumes perfect channel state information （CSI） at the transmitter or on limited feedback techniques, such as channel quantization or limited feedback signal designs. This paper proposes a novel unitary downlink precoding design scheme for multiuser spatial multiplexing multiple-input multiple-output （MIMO） systems. With the perfect CSI available at the transmitter and the linear decoder at the receiver, the cost function was constructed based on the minimum average probability of vector symbol error and the design method of the precoding matrices was given. These proposed precoding matrices can completely eliminate co-channel interference for each user at the transmitter, and each user will eventually observe an interference-free single user channel, thus simplify the decoding of each user. The impact of channel feedback errors on the system performance and the upper bounds of several schemes for performance comparison were investigated. The simulation results show that the proposed precoding for multiuser spatial multiplexing system obtains almost the same performance as the single user precoding system.

Unequal error protection scheme for layered sources transmission over MIMO systems using spatial diversity and multiplexing technology

This paper proposes a hybrid scheme of the Alamouti coding and vertical bell labs layered space-time （V-BLAST） with the zero-forcing （ZF） receiver, which can achieve the unequal error protection （UEP） transmission in terms of the differences of importance in the layered sources. We analyze the tradeoff between spatial diversity and multiplexing in a mathematical manner, and prove the monotonic behavior of the crosspoint. Based on this scheme, we adopt V-BLAST to provide high data rates for the enhancement layer （EL） bitstreams, and adopt Alamouti coding to guarantee high reliability for the base layer （BL） bitstreams. Meanwhile, to improve the transmission reliability for the layered sources under the multiple-input multiple-output （MIMO） system with the limited-bandwidth and the total limited power, and to raise the frequency bandwidth efficiency, we take the power allocation considered in this proposed scheme. The simulation results show that the hybrid scheme has the average 1.9 dB and 1.3 dB gain in video peak signal-to-noise ratio （PSNR）, compared with the pure spatial diversity and pure spatial multiplexing scheme, respectively.

Adaptive Mapping Generalized Space Shift Keying Modulation

Generalized Space Shift Keying （GSSK） modulation is a low-complexity spatial nmltiplexing technique for nmltiple-antenna wireless systems. However, effective transmit antenna combinations have to be preselected, and there exist redundant antenna combinations which are not used in GSSK. In this paper, a novel adaptive mapping scheme for GSSK modulation, named as Adaptive Mapping Generalized Space Shift Keying （AMGSSK）, is presented. Compared with GSSK, the antenna combinations are updated adaptively according to the Channel State Inforrmtion （CSI） in the proposed AMGSSK system, and the perfonrance of average Symbol Error Rate （SER） is reduced considerably. In the proposed scheme, two algorithrrs for selecting the optimum antenna combinations are described. The SER perfonmnce of AMGSSK is analyzed theoretically, and validated by Monte Carlo sinmlation. It is shown that the proposed AMGSSK scheme has good perfonmnce in SER and spectral efficiency.

Ergodic Capacity Evaluation of Multi-Hop Decode-and-Forward MIMO-OFDM Relaying Network

Spatial diversity plays a significant role in wireless communication systems,including the Fourth Generation(4G)and Fifth Generation(5G)systems,and it is expected to be a fundamental part of the future wireless communication systems as well.The Multiple-Input Multiple-Output(MIMO)technology,which is included in the IEEE 802.16j standard,still holds the most crucial position in the 4G spectrum as it promises to improve the throughput,capacity,spectral,and energy efficiency of wireless communication systems in the 2020s.This makes MIMO a viable technology for delay constrained medical and health care facilities.This paper presents an approximate closed-form expression of the ergodic capacity for the Decode-and-Forward(DF)protocol MIMO-Orthogonal Frequency Division Multiplexing(OFDM)relaying network.Although MIMO-OFDM is highly valuable for modern high-speed wireless communication systems,especially in the medical sciences,its performance degrades in multi-hop relay networks.Therefore,in this paper,an approximate closed-form expression is derived for an end-to-end ergodic capacity of multi-hop DF MIMO-OFDM wireless communication system has been presented.Monte-Carlo simulations are conducted to verify the performance of the presented analysis regarding the capacity(bits/s/Hz)for different SNR-dB values for single,2×2,4×4,and multi-hop DF MIMOOFDM systems.The presented results provide useful insights for the research on the end-to-end ergodic capacity evaluation.

Power duality for multi-antenna OFDM system in broadcast channel with user scheduling

This paper deals with design and analysis of user scheduling and power allocation for multi-antenna OFDM systems with DPC,ZF-DPC,ZF-BF and TDMA transmit strategies.We consider the general multi-user downlink scheduling problem and power minimization with multi-user rate constraints.According to the channel state,it is shown that there is a power optimal policy which selects a subset of users in each scheduling interval.We present user selection algorithms for DPC,ZF-DPC,ZF-BF and TDMA for multi-antenna OFDM system in broadcast channels,and we also present the practical water-filling solution in this paper.By the selected users with the consideration of fairness,we derive the power optimization algorithm with multi-user rate constraints.We also analyze the power duality of uplink-downlink for the transmit strategies of DPC,ZF-DPC and ZF-BF.Simulation results show that the present user-scheduling algorithm and power minimization algorithm can achieve good power performance,and that the scheduling algorithm can guarantee fairness.

Particle filter for joint frequency offset and channel estimation in MIMO-OFDM systems

A particle filter is proposed to perform joint estimation of the carrier frequency offset （CFO） and the channel in multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling （SIS）, and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling （SIR）. Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.

Antenna selection for V-BLAST systems in correlated channel

Spatial multiplexing systems can provide significant capacity improvement but are sensitive to channel correlation. Antenna selection is a low-cost low-complexity ahemative to resolve these problems. This paper proposes a new transmit antenna selection algorithm for the spatial multiplexing systems with the Vertical-Bell Labs Layered Space-Time （V-BLAST） nonlinear receiver in correlated channel. The proposed scheme separates the optimization into two parts： it first chooses the optimal number of substreams in terms of the singular values of the channel matrix, then adapts the mapping of substreams to antennas according to the post-detection signal-to-noise ratio （SNR）. Simulation results illustrate that the proposed two-step selection criterion can provide greater selection gain than the existing singnlar value based selection criterion as SNR and scattering angle increases. The proposed criterion outperforms the existing one by 0.3 dB at a vector symbol error rate of 10^- 3 and scattering angle of 20 degree.

Schemes for synthesizing high-resolution range profile with extended OFDM-MIMO

Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.

Suboptimal MMSE Channel Estimation with Subspace Tracking for MIMO-OFDM Transmission

A suboptimal minimum mean-squared error estimation （MMSE） is proposed for a dispersive wireless channel in the absence of its .orrelation matrix for multipleinput multiple-output ort,ogonal frequency division multiplexing （MIMO - OFDM） transmission. It utilizes a fast subspace approximation tracking to separate signal subspace with a limited set of channel estimates. The subspace rank is adjusted by pre-set thresholds in different signal-to-noise ratios （SNRs）. The performance comparison among the proposed algorithm, least square based, and the optimal MMSE estimation is shown by numerical simulation under a spatially correlated multi-tap channel scenario. It demonstrates that the approach has better normalized mean square error than recursive least square estimation and yields 3 dB gain over the latter.

Optimal Multipoint-to-Multipoint Transceiver Design with Massive MIMO Relay Station in OFDM Systems

Based on massive MIMO （ multiple-input multiple-output） （M2M） systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal mbearriers of OFDM （ orthogonal frequency division multiplexing） during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase. The massive M2M system included a single relay station, multiple paired source nodes and destination nodes. Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems. After some mathematical manipulation to sum-rate, the cost function of sum.rate was expressed as quadratic optimizing expressions which could be solved by regular convex optlmiTation softwares. Different from existing algorithms, the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement. Simulations indicate the effectiveness of the proposed optimal precoding system. The proposed scheme not only can reduce pilot contamination, but also can improve performance of bit-error-rate （BER） as wed as sum- rate contrast to existing algorithms. In addition, it shows that the proposed M2M massive MIMO system works steadily when the number of users increases in large scale.