JOINT ESTIMATION OF CARRIER FREQUENCY OFFSET AND POWER DELAY PROFILE FOR MIMO-OFDM SYSTEMS

This paper develops a Cyclic Prefix(CP)based joint Maximum-Likelihood(ML)estima-tion algorithm of Carrier Frequency Offset(CFO)and Power Delay Profile(PDP)for Multi-InputMulti-Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM)systems.However,theexact solution of the joint ML estimation is very complex since it needs a search over amulti-dimensional domain.Thus a simplified method is proposed to estimate the CFO and the PDPiteratively via the alternating-projection method which could induce the multidimensional searchproblem to a sequence of simple one-dimensional searches.Simulations show that the proposed algo-rithm is more accurate and robust than the existing algorithms.

SUBSPACE-BASED NOISE VARIANCE AND SNR ESTIMATION FOR MIMO OFDM SYSTEMS

This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The special training sequences with the property of orthogonality and phase shift orthogonality are used in pilot tones to obtain the estimated channel correlation matrix. Partitioning the observation space into a delay subspace and a noise subspace, we achieve the measurement of noise variance and SNR. Simulation results show that the proposed estimator can obtain accurate and real-time measurements of the noise variance and SNR for various multipath fading channels, demonstrating its strong robustness against different channels.

LMMSE-based SAGE channel estimation and data detection joint algorithm for MIMO-OFDM system

A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.

Experimental study of different turbo coding rates for MIMO-OFDM system

Multi-input multi-output orthogonal frequency division multiplexing（MIMO-OFDM）is the foremost space interface for 4Gand 5Gbroadband wireless communication.MIMO can transmit diverse signals over multiple antennas and OFDM can divide a radio channel into a huge number of closely spaced sub channels to afford more reliable communications at high speed.Research show that MIMO can be used with other well-liked wireless interfaces such as time division multiple access（TDMA）and code division multiple access（CDMA）,the amalgamation of MIMO and OFDM is most realistic at higher data rates.It is conclude that by using different turbo coding rate,we are getting improved bit error rate（BER）.

POWER ALLOCATION AND ADAPTIVE MODULATION STRATEGY FOR MIMO-OFDM SYSTEMS WITH IMPERFECT CSI

The presented scheme named M-CAP (Maximum CAPacity) uses the CSI (Channel State Information) and its statistics to deduce an equivalent channel according to which the transmit power is allocated to the subchannels. And then modulation scheme is determined adaptively according to the power allocated to each subchannel. The advantage of the M-CAP scheme is that it combines power allocation and adaptive modulation while maintaining a large capacity. We demonstrate by computer simulations that the proposed M-CAP scheme can significantly improve system performance compared with the traditional schemes.

An Indoor Environment Sensing and Localization System via mmWave Phased Array

In this paper,an indoor layout sensing and localization system with testbed in the 60-GHz millimeter wave(mmWave)band,named mmReality,is elaborated.The mmReality system consists of one transmitter and one mobile receiver,both with a phased array and a single radio frequency(RF)chain.To reconstruct the room layout,the pilot signal is delivered from the transmitter to the receiver via different pairs of transmission and receiving beams,so that multipath signals in all directions can be captured.Then spatial smoothing and the two-dimensional multiple signal classification(MUSIC)algorithm are applied to detect the angle-of-departures(AoDs)and angle-of-arrivals(AoAs)of propagation paths.Moreover,the technique of multi-carrier ranging is adopted to measure the path lengths.Therefore,with the measurements of the receiver in different locations of the room,the receiver and virtual transmitters can be pinpointed to reconstruct the room layout.Experiments show that the reconstructed room layout can be utilized to localize a mobile device via the AoA spectrum.