MIMO Detection Research Articles

Uplink bit combining for multiple base‐stations MIMO with applications to CoMP systems

AbstractThis work considers a simple bit level combining technique, aided by robust bit reliability information, for uplink collaborating multiple‐input multiple‐output (MIMO) base‐stations (also known as macrodiversity MIMO), operating over composite Rayleigh‐lognormal fading channels. Bit reliability weights based on a robust modification of the logarithmic likelihood ratio, combined with instantaneous symbol signal‐to‐noise ratio information, are derived for different local MIMO detection schemes. This bit reliability information is used at the fusion center, together with locally detected data, for combining and producing final information bits delivered to the destination. Computer simulation results confirm that such bit level combining techniques, when used with minimum mean squared error ordered successive interference cancelation and also with sphere decoding maximum likelihood local detectors, provide significant performance improvements over non‐collaborative base‐stations systems. Performance gains are maintained even when these schemes suffer from channel estimation errors and also in the presence of space correlation. Low backhaul overhead and performance advantages make these bit level combining techniques attractive for applications in next generation cellular systems employing coordinated multi‐point (CoMP) technology, as well as for other collaborative MIMO communication schemes.Copyright © 2014 John Wiley & Sons, Ltd.

Expectation Propagation Detection for High-Order High-Dimensional MIMO Systems

Modern communications systems use multiple-input multiple-output (MIMO) and high-order QAM constellations for maximizing spectral efficiency. However, as the number of antennas and the order of the constellation grow, the design of efficient and low-complexity MIMO receivers possesses big technical challenges. For example, symbol detection can no longer rely on maximum likelihood detection or sphere-decoding methods, as their complexity increases exponentially with the number of transmitters/receivers. In this paper, we propose a low-complexity high-accuracy MIMO symbol detector based on the Expectation Propagation (EP) algorithm. EP allows approximating iteratively at polynomial-time the posterior distribution of the transmitted symbols. We also show that our EP MIMO detector outperforms classic and state-of-the-art solutions reducing the symbol error rate at a reduced computational complexity.

A low complexity soft-output detection algorithm for 2×2 multiple-input multiple-output multiband-ofdm systems using dual carrier modulation

This paper presents a low complexity soft-output detection algorithm for 2×2 multiple-input multiple-output (MIMO) multiband-orthogonal frequency division multiplexing (MB-OFDM) systems using dual carrier modulation (DCM) or modified DCM (MDCM). By detecting each symbol pair of DCM or MDCM separately, the proposed detection algorithm reduces the complexity of the partial Euclidean distance (PED) calculation and the preprocessing complexity, which is the complexity of QR decomposition and channel ordering. This paper also proposes an efficient candidate list extension method for soft-output MIMO detection by using the calculated PEDs. Because the proposed algorithm has a low complexity and can also be implemented in a fully-pipelined hardware, the proposed algorithm is suitable for MB-OFDM systems requiring high speed hardware. The simulation results of applying the proposed algorithm to 2×2 MIMO MB-OFDM systems using DCM or MDCM show that the performance of the proposed algorithm has near soft-output maximum likelihood detection performance. The hardware complexity of the proposed algorithm is approximately 40% of that of the existing algorithm with similar performance.

Recent Advances in Design and Implementation of Signal Processing Systems

Advances in IC devices and technologies drive the need for innovation in design and implementation techniques for signal processing systems. Emerging signal processing algorithms place large demands on processing complexity, which must be met under strict area and power limits. To meet these challenges, more efficient algorithms and architectures are needed. This special issue contains a selection of papers on recent advances in the design and implementation of signal processing systems in the areas of wireless communications, phasechange memory, real-time vision, and error-correcting codes. In GPU Acceleration of a Configurable N-Way MIMO Detector for Wireless Systems Wu, Yin, Wang, Studer, and Cavallaro present an N-way MIMO detector for addressing the computational complexity of conventional detectors. Their implementations on practical GPUs highlight opportunities for parallelism, which in turn enable scalability in the detector algorithms, making energy and performance tradeoffs readily accessible . Even with the configurabi l i ty, their implementations outperform typical GPU-based MIMO detectors. In DIFFS: A Low Power, Multi-mode, Multi-standard Flexible Digital Front-end for Sensing in Future Cognitive Radios, Chiumento, Hollevoet, Pollin, Naessens, Dejonghe, and Van der Perre present the idea of a configurable digital front-end, capable of performing efficient spectrum sensing and synchronization to selectively trigger digital baseband functions in future cognitive radios. The authors propose a design that can support multiple modes and standards (LTE, WLAN, DVB-T), and they demonstrate an implementation in a custom IC in 65 nm CMOS. In Energy-adaptive Pulse Amplitude Modulation for IRUWB Communications under Renewable Energy, Zhao, Chen, and Wang present an energy adaptive Pulse Amplitude Modulation technique for self-powered Impulse Radio Ultra-wideband (IR-UWB) communication systems. By jointly exploiting the wireless channel conditions and the non-deterministic characteristics of renewable energy sources, the proposed technique can effectively improve the communication system data rate and/or time coverage. Yang, Emre, Xu, Chen, Cao, and Chakrabarti present a cost-effective solution for improving the reliability of multibit per cell phase change RAM (PRAM) in A Low Cost MultiTiered Approach To Improving The Reliability Of Multi-Level Cell PRAM. Error models are first developed to accurately capture hard and soft errors in multi-bit per cell PRAM, based upon which a variety design techniques across circuit, architecture, and system are developed to improve the data storage reliability at minimal speed, silicon, and energy overhead. The effectiveness is well demonstrated through comprehensive evaluations. In Accelerating Multiresolution Gabor Feature Extraction for Real Time Vision Applications Cho, Chandramoorthy, W. J. Gross (*) Department of Electrical and Computer Engineering, McGill University, Montreal, Quebec, Canada e-mail: warren.gross@mcgill.ca

Algorithms and Architectures of Energy-Efficient Error-Resilient MIMO Detectors for Memory-Dominated Wireless Communication Systems

In a broadband MIMO-OFDM wireless communication system, embedded buffering memories occupy a large portion of the chip area and a significant amount of power consumption. Due to process variations of advanced CMOS technologies, it becomes both challenging and costly to maintain perfectly functioning memories under all anticipated operating conditions. Thus, Voltage over Scaling (VoS) has emerged as a means to achieve energy efficient systems resulting in a tradeoff between energy efficiency and reliability. In this paper we present the algorithm and VLSI architecture of a novel error-resilient K-Best MIMO detector based on the combined distribution of channel noise and induced errors due to VoS. The simulation results show that, compared with a conventional MIMO detector design, the proposed algorithm provides up-to 4.5 dB gain to achieve the near-optimal Packet Error Rate (PER) performance in the 4 × 4 64-QAM system. Furthermore, based on experimental results, when jointly considering the detector and memory power consumption, the proposed resilient scheme with VoS memory can achieve up to 32.64% savings compared to the conventional K-Best detector with perfect memory.

A Mathematical modeling and Simulation Analysis of Lattice reduction algorithms for large MIMO detections

Abstract – This paper analyses the performance of Multiple Input Multiple Output (MIMO) wireless communication system by combining it with an efficient algorithm Diagonal Reduction (DR). DR is a powerful tool to achieve more efficiently a high performance with less complexity. This paper proposes a DR algorithm in order to reduce its complexity named Greedy Diagonal Reduction (GDR) algorithm which gives reduced complexity with efficient performance at the receiver using the MATLAB communication tool box version 7.0 as a simulation tool. From the simulation results of various reduction algorithms it is observed that, DR can reduce the number of iterations using size reduction operations. Proposed DR algorithm gives identical Bit Error Rate (BER) performance with LLL algorithms when applied to Successive Interference cancellation (SIC) decoding. Greedy DR reduces the computational complexity in Multiple Input Multiple Output systems by improving the efficiency in terms of size reduction operations. Sphere Decoding (SD) technique gives better BER performance on comparing with Successive Interference cancellation decoding technique.

Full-Diversity Approximated Lattice Reduction Algorithm for Low-Complexity MIMO Detection

In this letter, we propose a new approximated basis vector reordering (ABVR) criterion for low-complexity lattice reduction aided (LRA) multiple-input multiple-output (MIMO) detection. Despite the approximation, the ABVR criterion is proved to collect the full receiving diversity for LRA linear detection. A variant of the well-known complex Lenstra Lenstra Lovász (CLLL) algorithm, i.e., LLL with deep insertion (DLLL), is employed to accommodate the ABVR criterion (DLLL-ABVR). Compared with the original CLLL and other approximated algorithms, the proposed DLLL-ABVR algorithm largely reduces the number of basis vector reordering (BVR) operations. Simulation results show that, on a practical MIMO scale, the proposed lattice reduction algorithm provides similar detection performance, especially for successive interference cancelation (SIC) detectors, while requiring significantly lower computational complexity.

A low‐complexity iterative MIMO detection and decoding scheme using dimension reduction

AbstractSpatial multiplexing multiple‐input multiple‐output is considered as a core advanced communication technology to increase data rate. Although it guarantees higher capacity, it gives huge burden on the receiver side especially when iterative detection and decoding (IDD) is employed. Therefore, the IDD receiver needs to be efficiently implemented considering the complexity as well as performance in practice. In this paper, we propose an IDD scheme employing dimension reduction soft demodulation (DRSD) principle based on maximum a posteriori criterion necessary for IDD operation. With separation into hard and soft streams in the DRSD, the proposed scheme employs all ordering successive interference cancellation with a simple modified slicing for hard detection to consider the effect of a priori information conveyed from past iteration, enabling complexity reduction. It can provide better trade‐off between complexity and performance. Copyright © 2014 John Wiley & Sons, Ltd.

GPU Acceleration of a Configurable N-Way MIMO Detector for Wireless Systems

Multiple-input multiple-output (MIMO) wireless is an enabling technology for high spectral efficiency and has been adopted in many modern wireless communication standards, such as 3GPP-LTE and IEEE 802.11n. However, (optimal) maximum a-posteriori (MAP) detection suffers from excessively high computational complexity, which prevents its deployment in practical systems. Hence, many algorithms have been proposed in the literature that trade-off performance versus detection complexity. In this paper, we propose a flexible N-Way MIMO detector that achieves excellent error-rate performance and high throughput on graphics processing units (GPUs). The proposed detector includes the required QR decomposition step and a tree-search detector, which exploits the massive parallelism available in GPUs. The proposed algorithm performs multiple tree searches in parallel, which leads to excellent error-rate performance at low computational complexity on different GPU architectures, such as Nvidia Fermi and Kepler. We highlight the flexibility of the proposed detector and demonstrate that it achieves higher throughput than existing GPU-based MIMO detectors while achieving the same or better error-rate performance.

Antenna placement and power allocation optimization in MIMO detection

It is a well known fact that using multiple antennas at transmit and receive sides improves the detection performance. However, in such multiple-input multiple-output (MIMO) configuration, proper positioning of transmitters and receivers is a big challenge that can have significant influence on the performance of the overall system. In addition, determining the power of each transmitter under a total power constraint is a problem that should be solved in order to enhance the performance and coverage of such a system. In this paper, we design the Neyman-Pearson detector under the Rayleigh scatter model and use it to introduce a criterion for the antenna placement at both transmit and receive sides. We then show that by using a waterfilling-type algorithm at the detector's output, optimum transmitter powers can be determined accordingly.

MIMO 검출기에 적용 가능한 저 복잡도 복합 QR 분해 구조

본 논문에서는 MIMO 검출기를 위한 저 복잡도 QR 분해 구조를 제시한다. 제안된 접근 방식에서는, QRD 하드웨어의 연산 복잡도를 감소시키기 위해 다양한 코딕 기반 QRD 알고리즘들이 효율적으로 조합된다. 다양한 QRD 알고리즘들에 대한 연산 복잡도 분석에 기초하여, QRD 과정의 매 단계마다 저 복잡도 접근 방식이 선택된다. 제안된 QRD 구조는 어떤 임의의 차원을 갖는 채널 매트릭스에도 적용 될 수 있고, 매트릭스 차원의 증가에 따라 연산 복잡도 감소도 늘어난다. 제안하는 QR 분해 하드웨어는 삼성 <TEX>$0.13{\mu}m$</TEX> 공정을 사용하여 구현되었다. 실험결과, <TEX>$4{\times}4$</TEX> 행렬의 QR 분해에 대한 제안 구조는 기존의 Householder 코딕 기반의 구조에 비해 47%의 QAR(QRD Rate/Gate count) 향상과 28%의 전력을 절감을 이뤄낼 수 있었다. This paper presents a low complexity QR decomposition (QRD) architecture for MIMO detector. In the proposed approach, various CORDIC-based QRD algorithms are efficiently combined together to reduce the computational complexity of the QRD hardware. Based on the computational complexity analysis on various QRD algorithms, a low complexity approach is selected at each stage of QRD process. The proposed QRD architecture can be applied to any arbitrary dimension of channel matrix, and the complexity reduction grows with the increasing matrix dimension. Our QR decomposition hardware was implemented using Samsung <TEX>$0.13{\mu}m$</TEX> technology. The numerical results show that the proposed architecture achieves 47% increase in the QAR (QRD Rate/Gate count) with 28.1% power savings over the conventional Householder CORDIC-based architecture for the <TEX>$4{\times}4$</TEX> matrix decomposition.

Study on MIMO transmission using orthogonal directivities obtained from higher order microstrip antenna modes

A simpler MIMO transmission method using orthogonal directivities is proposed. In future wireless communication systems, higher data rates will be required since large amounts of data will be transmitted and received. MIMO technology is useful for achieving higher data rates. However, since MIMO detection becomes complicated when the number of antennas becomes large, a simpler method should be considered. To solve this problem, the present authors proposed a spatial division method using orthogonal directivities. This previously proposed method to N streams is expanded transmission for application to much higher data rate systems. Furthermore, using higher order antenna modes at the same frequency to more easily obtain orthogonal directivities is proposed. To evaluate the proposed method, it is confirmed by numerical analysis that the capacity of the proposed method increases without MIMO detection when the number of antennas becomes large.

Approximate maximum a posteriori detection for multiple‐input–multiple‐output systems with bit‐level lattice reduction‐aided detectors and successive interference cancellation

For iterative detection and decoding (IDD) in multiple-input–multiple-output (MIMO) systems, although the maximum a posteriori (MAP) detector can achieve an optimal performance, because of its prohibitively high computational complexity, various low-complexity approximate MAP detectors are studied. Among the existing MIMO detectors for the non-IDD receivers, lattice reduction (LR)-aided detectors can provide a near maximum-likelihood (ML) detector's performance with reasonably low complexity, and they could be modified to be used in the IDD receivers. In this study, the authors propose a bit-level LR-aided MIMO detector whose performance can approach that of the MAP detector, where a priori information is taken into account for soft-decisions. Furthermore, the proposed method can be extended to large dimensional MIMO systems by channel matrix decomposition and successive interference cancellation, by which a significant complexity reduction can be achieved. Through simulations and complexity analysis, it is shown that a near-optimal performance is obtained by the authors proposed low-complexity bit-level LR-aided detector for the IDD in the MIMO systems.

Lattice‐reduction‐aided semidefinite relaxation detection algorithms for multiple‐input multiple‐output systems

Multiple-input multiple-output (MIMO) system is considered to be one of the key technologies of long-term evolution, since it achieves requirements of high throughput and spectral efficiency. The semidefinite relaxation (SDR) detection for MIMO systems is an attractive alternative to the optimum maximum likelihood (ML) decoding because it is very computationally efficient. In the case of the binary phase shift keying and four quadrature amplitude modulation constellations, the block error rate (BLER) performance of SDR detection is fairly close to the optimum BLER performance. However, for high-order modulation systems, their BLER performance is still unsatisfactory compared with the ML decoding. Lattice reduction technology can transform a matrix into a new equivalent one with more orthogonal and shorter basis vectors. It has been combined with linear decoders to improve their BLER performance. Inspired by this, the authors proposed two lattice-reduction-aided MIMO detection algorithms based on SDR. Simulation results demonstrate that they can provide near-optimum BLER performance with polynomial time complexity.

Stochastic MIMO Detector Based on the Markov Chain Monte Carlo Algorithm

A stochastic computing framework for a Markov Chain Monte Carlo (MCMC) multiple-input-multiple-output (MIMO) detector is proposed, in which the arithmetic operations are implemented by simple logic structures. Specifically, we introduce two new techniques, namely a sliding window generator (SWG) and a log-likelihood ratio based updating method (LUM), to achieve an efficient design. The SWG utilizes the variance in stochastic computations to increase the transition probability of the MCMC detector, while the LUM reduces the hardware cost. As a case study, we design a fully-parallel stochastic MCMC detector for a 4 ×4 16-QAM MIMO system using 130 nm CMOS technology. The proposed detector achieves a throughput of 1.5 Gbps with only a 0.2 dB performance loss compared to a traditional floating-point detection method. Our design has a 30% better ratio of gate count to scaled throughput compared to other recent MIMO detectors.

Analog joint source-channel coding over MIMO channels

Analog joint source-channel coding (JSCC) is a communication strategy that does not follow the separation principle of conventional digital systems but has been shown to approach the optimal distortion-cost tradeoff over additive white Gaussian noise channels. In this work, we investigate the feasibility of analog JSCC over multiple-input multiple-output (MIMO) fading channels. Since, due to complexity constraints, directly recovering the analog source information from the MIMO channel output is not possible, we propose the utilization of low-complexity two-stage receivers that separately perform detection and analog JSCC maximum likelihood decoding. We study analog JSCC MIMO receivers that utilize either linear minimum mean square error or decision feedback MIMO detection. Computer experiments show the ability of the proposed analog JSCC receivers to approach the optimal distortion-cost tradeoff both in the low and high channel signal-to-noise ratio regimes. Performance is analyzed over both synthetically computer-generated Rayleigh fading channels and real indoor wireless measured channels.

Toward Multi-Gigabit Wireless: Design of High-Throughput MIMO Detectors With Hardware-Efficient Architecture

This paper presents a hardware-efficient architecture for 4×4 and 8×8 high-throughput MIMO detectors. The adopted non-constant K-best algorithm tends to keep more survival nodes in top search tree layers and reduce computational complexity in bottom layers as opposed to the conventional K-best algorithm. A pipelined architecture is used to generate one detection output per clock cycle, thus meeting multi-gigabit throughput requirements for advanced wireless communication systems. The proposed efficient folding scheme strikes a suitable balance between complexity and throughput. This paper also presents a discussion on the scalability of this architecture with respect to the setting of QAM size, K values, and antenna number. One 4×4 MIMO detector IC has been manufactured and one 8×8 MIMO detector layout has been realized, both in 90-nm CMOS technology. The 4×4 detector IC has 232 kilogates (KG). Its maximum measured throughput is 4.08 Gbps at 170-MHz operating frequency and 1.3-V core voltage. The 8×8 detector has 665 KG. Its post-layout simulation results show that it achieves 4.37-Gbps throughput at 182-MHz operating frequency and 0.9-V core voltage. Compared to earlier hard-output detectors, both implemented detectors demonstrate good normalized power and normalized hardware efficiencies.

A Semifixed Complexity Sphere Decoder for Uncoded Symbols for Wireless Communications

The development of high data rate wireless communications systems using Multiple Input — Multiple Output (MIMO) antenna techniques requires detectors with reduced complexity and good Bit Error Rate (BER) performance. In this paper, we present the Semi-fixed Complexity Sphere Decoder (SCSD), which executes the process of detection in MIMO systems with a significantly lower computation cost than the high-performance/reduced-complexity detectors: Sphere Decoder (SD), K-best, Fixed Complexity Sphere Decoder (FSD) and Adaptive Set Partitioning (ASP). Simulation results show that when the Signal-to-Noise Ratio (SNR) is less than 15dB, the SCSD reduces the complexity by up to 90% with respect to SD, up to 60% with respect to K-best or ASP and by up to 90% with respect to FSD. In the proposed algorithm, the BER performance does not show significant degradation and therefore, can be considered as a complexity reduction scheme suitable for implementing in MIMO detectors.

A Fractional Lower Order Statistics-Based MIMO Detection Method in Impulse Noise for Power Line Channel

Impulse noise in power line communication (PLC) channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO) system. To remedy this problem, a MIMO detection meth ...

Theoretical and experimental analysis of spatial division using antenna directivities in short‐range MIMO transmission

A simple method is proposed for achieving short-range multiple-input multiple-output (MIMO) transmission without complicated signal processing. This is achieved by a spatial division that cancels interference between signal streams by using π-phase-shifted antenna directivities in high speed parallel transmission systems at 60 GHz. The method achieves spatial division transmission without MIMO detection even for antenna elements with wide beamwidths. This makes it easy to design antenna elements and reduces signal processing costs in the transmitter and the receiver. Moreover, the method provides almost the same channel capacity as that of the complicated MIMO transmission methods. The optimal antenna array length is derived to maximise the capacity and the validity of the proposed method is confirmed through numerical and experimental analyses at 4.85 GHz.