This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-inputmultiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID ...
详细信息
This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-inputmultiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC ***, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.
Grant-free non-orthogonal multiple access (GF-NOMA) and multiple-inputmultiple-output (MIMO) techniques are key enablers for massive machine-type communications (mMTC) in 5G cellular Internet of Things. On the other ...
详细信息
Grant-free non-orthogonal multiple access (GF-NOMA) and multiple-inputmultiple-output (MIMO) techniques are key enablers for massive machine-type communications (mMTC) in 5G cellular Internet of Things. On the other hand, compressed sensing (CS) is widely accepted for multiuser detection, due to the sporadic traffic of mMTC. In this letter, we propose two Bayesian-based CS algorithms for uplink grant-free MIMO-NOMA. Exploiting the iterative expectation maximization (EM) and maximum ratio combining techniques, the spatially enhanced sparse Bayesian learning (SE-SBL) algorithm is developed to alternately update hyperparameter values and combined observation signals. Furthermore, we embed the generalized approximate message passing technique into the SE-SBL and propose a low-complexity computational approach. In particular, the aforementioned Bayesian algorithms do not require any prior knowledge of user activity level and noise power. Simulation results show that the proposed Bayesian methods exhibit a superior performance gain over the state-of-the-art.
This paper presents a novel cooperation optimization formulation for the multiple-inputmultiple-output (MIMO) radar and MIMO communication system spectrum coexistence. To optimize the communication rate and the radar...
详细信息
ISBN:
(纸本)9781665426718
This paper presents a novel cooperation optimization formulation for the multiple-inputmultiple-output (MIMO) radar and MIMO communication system spectrum coexistence. To optimize the communication rate and the radar filtered interference power (FIP) simultaneously, the radar transmitreceive beamforming and communication codebook are jointly optimized with the constrained weighted sum design. To solve the nontrivial multi-variables problem, an alternating iteration is derived that allows to decompose the non-convex optimizations into three suitably designed sub-problems, whose solutions are provided in closed-form. Finally, numerical results are provided to illustrate the merits of the proposed approach and validate the theoretical analyses.
In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division multiplexing（OFDM） multiple-inputmultiple-Output（MIMO） radar system in multi-target scene, we propose a novel a...
详细信息
In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division multiplexing（OFDM） multiple-inputmultiple-Output（MIMO） radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design（AWD） based on a constrained Multi-Objective Optimization（MOO）. The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.
High pulse repetition frequency incurs range ambiguity in radar systems, which in turn results in clutter suppression performance degradation and parameter estimation ambiguities. To tackle this issue, this paper prop...
详细信息
High pulse repetition frequency incurs range ambiguity in radar systems, which in turn results in clutter suppression performance degradation and parameter estimation ambiguities. To tackle this issue, this paper proposes an adaptive range-angle-Doppler processing approach with airborne frequency diverse array (FDA) for multiple-inputmultiple-output (MIMO) radar. The FDA employs a small frequency increment across array elements and introduces additional controllable degrees-of-freedom (DOFs) in range dimension in the transmit antenna. Thus, it is able to perform range-angle-Doppler processing by exploiting the DOFs in transmit, receive, and pulse dimensions in the FDA-MIMO radar. By properly designing the frequency increment of the FDA, the clutter spectra of different ambiguous range regions can be discriminable in the transmit-receive spatial domains. As a result, multiple beams are formed in the transmit spatial, receive spatial, and Doppler domains and clutters from different range regions can be suppressed. An enhanced three-dimensional localization technique is proposed for the case with severe range ambiguity problem, which evidently reduces the dimensions of the processor and efficiently suppresses clutter in practical applications. Several numerical examples are presented to verify the effectiveness of the proposed approach.
In this paper, Pareto-optimal beamforming in the K-pair Gaussian multiple-inputmultiple-output (MIMO) interference channel is considered. Under the assumption of Gaussian signaling at transmitters and single-user dec...
详细信息
ISBN:
(纸本)9781479903566
In this paper, Pareto-optimal beamforming in the K-pair Gaussian multiple-inputmultiple-output (MIMO) interference channel is considered. Under the assumption of Gaussian signaling at transmitters and single-user decoding at receivers, a necessary condition for any transmit signal covariance matrix to achieve a Parcto boundary point of the achievable rate region is derived. Based on the necessary condition for Pareto-optimality, an efficient parameterization for Pareto-optimal transmit signal covariance matrices is obtained. The obtained parameter space is given by the product manifold of a Stiefel manifold and a subset of a hyperplane, which is a low dimensional embedded submanifold of the original high dimensional beam search space. The new parameterization enables us to devise very efficient beam design algorithms for the K-pair MIMO interference channel.
This paper studies a nonlinear vector precoding scheme which inverts the wireless multiple-inputmultiple-output (MIMO) channel at the transmitter so that simple symbol-by-symbol detection can be used in lieu of sophi...
详细信息
This paper studies a nonlinear vector precoding scheme which inverts the wireless multiple-inputmultiple-output (MIMO) channel at the transmitter so that simple symbol-by-symbol detection can be used in lieu of sophisticated multiuser detection at the receiver. In particular, the transmit energy is minimized by relaxing the transmitted symbols to a larger alphabet for precoding, which preserves the minimum signaling distance. The so-called replica method is used to analyze the average energy savings with random MIMO channels in the large-system limit. It is found that significant gains can be achieved with complex-valued alphabets. The analysis applies to a very general class of MIMO channels, where the statistics of the channel matrix enter the result via the R-transform of the asymptotic empirical distribution of its eigenvalues. Moreover, we introduce polynomial -complexity precoding schemes for binary and quadrature phase-shift keying in complex channels by using convex rather than discrete relaxed alphabets. In case the number of transmit antennas is more than twice the number of receive antennas, we show that a convex precoding scheme, despite its polynomial complexity, outperforms NP-hard precoding using the popular Tomlinson-Harashima signaling.
暂无评论