A Fuzzy MOE Receiver for Uplink MC-CDMA Systems with Carrier Frequency Offset over Multipath Fading Channels

A novel fuzzy minimum output energy (MOE) detector is proposed for uplink multicarrier CDMA (MC-CDMA) systems with carrier frequency offset (CFO) over multipath fading channels. The proposed receiver involves the following stages. First, the fuzzy CFO constrained MOE detector after coarse CFO estimation is proposed to suppress multiple access interference and combat the degradation problem of the conventional MOE detector caused by the CFO effect. Next, using the signal subspace projection technique, the proposed detector can further reduce the enhanced noise due to the fuzzy CFO constrained detector. Finally, the output data obtained from these detectors are coherently combined to offer multipath diversity gain in accordance with the maximum ratio combining criterion. Furthermore, the proposed single input single output (SISO) robust detector can be easily extended for a multiple input multiple output (MIMO) MC-CDMA system with a high rate of performance. Simulation results show that the proposed SISO detector, which offers a similar performance as the optimal detector, can provide robustness against CFO and outperform the conventional detectors. The proposed MIMO detector with spatial multiplexing gain also exhibits excellent performance.     

Low‐complexity turbo detection for single‐carrier low‐density parity‐check‐coded multiple‐input multiple‐output underwater acoustic communications

A low‐complexity turbo detection scheme is proposed for single‐carrier multiple‐input multiple‐output (MIMO) underwater acoustic (UWA) communications using low‐density parity‐check (LDPC) channel coding. The low complexity of the proposed detection algorithm is achieved in two aspects: first, the frequency‐domain equalization technique is adopted, and it maintains a low complexity irrespective of the highly dispersive UWA channels; second, the computation of the soft equalizer output, in the form of extrinsic log‐likelihood ratio, is performed with an approximating method, which further reduces the complexity. Moreover, attributed to the LDPC decoding, the turbo detection converges within only a few iterations. The proposed turbo detection scheme has been used for processing real‐world data collected in two different undersea trials: WHOI09 and ACOMM09. Experimental results show that it provides robust detection for MIMO UWA communications with different modulations and different symbol rates, at different transmission ranges. Copyright © 2011 John Wiley & Sons, Ltd.     

Low‐Complexity Massive MIMO Detectors Based on Richardson Method

In the uplink transmission of massive (or large‐scale) multi‐input multi‐output (MIMO) systems, large dimensional signal detection and its hardware design are challenging issues owing to the high computational complexity. In this paper, we propose low‐complexity hardware architectures of Richardson iterative method‐based massive MIMO detectors. We present two types of massive MIMO detectors, directly mapped (type1) and reformulated (type2) Richardson iterative methods. In the proposed Richardson method (type2), the matrix‐by‐matrix multiplications are reformulated to matrix‐vector multiplications, thus reducing the computational complexity from O(U²) to O(U). Both massive MIMO detectors are implemented using a 65 nm CMOS process and compared in terms of detection performance under different channel conditions (high‐mobility and flat fading channels). The hardware implementation results confirm that the proposed type1 Richardson method‐based detector demonstrates up to 50% power savings over the proposed type2 detector under a flat fading channel. The type2 detector indicates a 37% power savings compared to the type1 under a high‐mobility channel.     

Energy‐efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple‐input multiple‐output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space‐time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple‐input multiple‐output (MIMO) data transmission technique in the WSNs. The DSC‐MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC‐MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single‐input single‐output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.     

On the better protection of short-frame turbo codes

Protecting short data frames by turbo coding is a challenging task because of the small interleaver size and the need for transmission efficiency. In this letter, turbo-decoding-metrics aided short cyclic redundancy check codes are applied to novel tailbiting encoded trellis codes with a twofold purpose: to stop the iterative decoding processes to achieve low-power design and to reduce fractional coding-rate loss. Significant coding gains can be achieved by actually increasing the transmission rate with a negligible increase in power consumption. Performance improvement is demonstrated over additive white Gaussian noise channels. The savings is up to 21.4% for the transmission throughput and 21.5% for the energy consumption of the turbo decoder when frame size 49 is used.     

An application of univariate marginal distribution algorithm in MIMO communication systems

The paper discusses a sequence detector based on univariate marginal distribution algorithm (UMDA) that jointly estimates the symbols transmitted in a multiple input multiple output (MIMO) communication system. While an optimal maximum likelihood detection using an exhaustive search method is prohibitively complex, it has been shown that sphere decoder (SD) achieves the optimal bit error rate (BER) performance with polynomial time complexity for smaller array sizes. However, the worst‐case complexity of SD is exponential in the problem dimensions, this brings in question its practical implementation for larger number of spatial layers and for higher‐order signal constellation. The proposed detector shows promising results for this overly difficult and complicated operating environment, confirmed through simulation results. A performance comparison of the UMDA detector with SD is presented for higher‐order complex MIMO architectures with limited average transmit power. The proposed detector achieves substantial performance gain for higher‐order systems attaining a near optimal BER performance with reduced computational complexity as compared with SD. Copyright © 2009 John Wiley & Sons, Ltd.     

Low‐Power Channel‐Adaptive Reconfigurable 4×4 QRM‐MLD MIMO Detector

This paper presents a low‐complexity channel‐adaptive reconfigurable QR‐decomposition and M‐algorithm‐based maximum likelihood detection (QRM‐MLD) multiple‐input and multiple‐output (MIMO) detector. Two novel design approaches for low‐power QRM‐MLD hardware are proposed in this work. First, an approximate survivor metric (ASM) generation technique is presented to achieve considerable computational complexity reduction with minor BER degradation. A reconfigurable QRM‐MLD MIMO detector (where the M‐value represents the number of survival branches in a stage) for dynamically adapting to time‐varying channels is also proposed in this work. The proposed reconfigurable QRM‐MLD MIMO detector is implemented using a Samsung 65 nm CMOS process. The experimental results show that our ASM‐based QRM‐MLD MIMO detector shows a maximum throughput of 288 Mbps with a normalized power efficiency of 10.18 Mbps/mW in the case of MIMO with 64‐QAM. Under time‐varying channel conditions, the proposed reconfigurable MIMO detector also achieves average power savings of up to 35% while maintaining a required BER performance.     

A simple soft linear detection for coded multi‐input multi‐output systems

We propose a very simple and efficient soft linear multi‐input multi‐output (MIMO) detection scheme. The detection process is divided into two separate problems. The proposed scheme first detects MIMO symbols using conventional linear detection methods and produces soft bit information using a simple soft demapping method. Next, we refine the soft information by accounting for uneven post‐detection noise variance across MIMO layers. From the simulation result investigated in this paper, we first emphasize that powerful channel coding may suppress the differences of diversity gains among various MIMO detection schemes. This implies that the channel decoding operation may not be transparent to performance gain that resulted from MIMO detection process. The proposed scheme concentrates on accurate estimation of soft post‐MIMO detected information in a very simple manner, rather than concentrating on a complex MIMO detection scheme prior to decoding process. In combination with turbo codes, the proposed scheme produces comparable performance to maximum likelihood detection, even with the simplest scheme such as zero forcing detection, with drastically reduced complexity. Copyright © 2011 John Wiley & Sons, Ltd.     

Layered MAP algorithm for MIMO ISI channels

The layered maximum a posteriori （L-MAP） algorithm has been proposed to detect signals under frequency selective fading multiple input multiple output （MIMO） channels. Compared to the optimum MAP detector, the L-MAP algorithm can efficiently identify signal bits, and the complexity grows linearly with the number of input antennas. The basic idea of L-MAP is to operate on each input sub-stream with an optimum MAP sequential detector separately by assuming the other streams are Gaussian noise. The soft output can also be forwarded to outer channel decoder for iterative decoding. Simulation results show that the proposed method can converge with a small number of iterations under different channel conditions and outperforms other sub-optimum detectors for rank-deficient channels.     

Efficient Implementation of a Pseudorandom Sequence Generator for High‐Speed Data Communications

A conventional pseudorandom sequence generator creates only 1 bit of data per clock cycle. Therefore, it may cause a delay in data communications. In this paper, we propose an efficient implementation method for a pseudorandom sequence generator with parallel outputs. By virtue of the simple matrix multiplications, we derive a well‐organized recursive formula and realize a pseudorandom sequence generator with multiple outputs. Experimental results show that, although the total area of the proposed scheme is 3% to 13% larger than that of the existing scheme, our parallel architecture improves the throughput by 2, 4, and 6 times compared with the existing scheme based on a single output. In addition, we apply our approach to a 2×2 multiple input/multiple output (MIMO) detector targeting the 3rd Generation Partnership Project Long Term Evolution (3GPP LTE) system. Therefore, the throughput of the MIMO detector is significantly enhanced by parallel processing of data communications.     

An FPGA Implementation of High‐Speed Flexible 27‐Mbps 8‐StateTurbo Decoder

In this paper, we propose a flexible turbo decoding algorithm for a high order modulation scheme that uses a standard half‐rate turbo decoder designed for binary quadrature phase‐shift keying (B/QPSK) modulation. A transformation applied to the incoming I‐channel and Q‐channel symbols allows the use of an off‐the‐shelf B/QPSK turbo decoder without any modifications. Iterative codes such as turbo codes process the received symbols recursively to improve performance. As the number of iterations increases, the execution time and power consumption also increase. The proposed algorithm reduces the latency and power consumption by combination of the radix‐4, dual‐path processing, parallel decoding, and early‐stop algorithms. We implement the proposed scheme on a field‐programmable gate array and compare its decoding speed with that of a conventional decoder. The results show that the proposed flexible decoding algorithm is 6.4 times faster than the conventional scheme.     

Energy Efficient VLSI Architecture for Linear Turbo Equalizer

In this paper, energy efficient VLSI architectures for linear turbo equalization are studied. Linear turbo equalizers exhibit dramatic bit error rate (BER) improvement over conventional equalizers by enabling a form of joint equalization and decoding in which soft information is iteratively exchanged between the equalizer and decoder. However, turbo equalizers can be computationally complex and hence require significant power consumption. In this paper, we present an energy-efficient VLSI architecture for such linear turbo equalizers. Key architectural techniques include elimination of redundant operations and early termination. Early termination enables powering down parts of the soft-input soft-output (SISO) equalizer and decoder thereby saving power. Simulation results show that energy savings in the range 30–60% and 10–60% are achieved in equalization and decoding, respectively. Furthermore, we present finite precision requirements of the linear turbo equalizer and an efficient rescaling method to prevent overflow.     

On the complexity reduction of turbo decoding for wideband CDMA

Two simple but effective methods for reducing the average complexity (and power consumption) of the conventional turbo-cyclic-redundancy-check decoding scheme with negligible performance degradation in a wideband direct-sequence code-division multiple-access (W-CDMA) environment are introduced. When applied to a W-CDMA turbo code with frame length 640 b at a bit-error rate (BER) of 10/sup -6/, the resultant modified schemes can save up to 73% of the average decoding complexity, relative to the conventional scheme. In general, the proposed schemes are more attractive for short-frame and low-BER applications.     

Efficient SIC-MMSE MIMO detection with three iterative loops

In this paper, we propose an efficient joint iterative detection and decoding (JIDD) scheme with a soft interference cancellation minimum mean squared error (SIC-MMSE) based method for a turbo coded multiple-input multiple-output (MIMO) system. In the proposed method, we activate a loop inside the SIC-MMSE based MIMO detection process in addition to the iterative loop between the MIMO detector and turbo decoder, so that the iteration inside the SIC-MMSE detection can be performed in parallel to the iterations inside the turbo decoder. Subsequently, soft outputs from each loop is exchanged for next further iteration, and this makes three iterative loops in total. In comparison with the conventional JIDD schemes, employing additional loop inside the MIMO detection process largely contributes to enhance the performance. In addition, the additional loop speeds up the performance convergence and eventually requires smaller overall computational complexity at the same performance.     

A low power turbo/Viterbi decoder for 3GPP2 applications

This paper presents a channel decoder that completes both turbo and Viterbi decodings, which are pervasive in many wireless communication systems, especially those that require very low signal-to-noise ratios. The trellis decoding algorithm merges them with less redundancy. However, the implementation is still challenging due to the power consumption in wearable devices. This research investigates an optimized memory scheme and rescheduled data flow to reduce power consumption and chip area. The memory access is reduced by buffering the input symbols, and the area is reduced by reducing the embedded interleaver memory. A test chip is fabricated in a 1.8 V 0.18-/spl mu/m standard CMOS technology and verified to provide 4.25-Mb/s turbo decoding and 5.26-Mb/s Viterbi decoding. The measured power dissipation is 83 mW, while decoding a 3.1 Mb/s turbo encoded data stream with six iterations for each block. The power consumption in Viterbi decoding is 25.1 mW in the 1-Mb/s data rate. The measurement shows the power dissipation is 83 mW for the turbo decoding with six iterations at 3.1 Mb/s, and 25.1 mW for the Viterbi decoding at 1 Mb/s.     

Implementation of parallel lattice reduction-aided MIMO detector using graphics processing unit

Since H. Yao proposed the lattice reduction (LR)-aided detection algorithm for the MIMO detector, one can exploit the diversity gain provided by the LR method to achieve performance comparable to the maximum likelihood (ML) algorithm but with complexity close to the simple linear detection algorithms such as zero forcing (ZF), minimum mean squared error, and successive interference cancellation, etc. In this paper, in order to reduce the processing time of the LR-aided detector, a graphics processing unit (GPU) has been proposed as the main modem processor in such a way that the detections can be performed in parallel using multiple threads in the GPU. A 2X2 multiple input multiple output (MIMO) WiMAX system has been implemented using a GPU to verify that various MIMO detection algorithms such as ZF, ML, and LR-aided methods can be processed in real-time. From the experimental results, we show that GPUs can realize a 2X2 WiMAX MIMO system adopting an LR-aided detector in real-time. We achieve a processing time of 2.75?ms which meets the downlink duration specification of 3?ms. BER performance of experimental tests also indicates that the LR-aided MIMO detector can fully exploit diversity gain as well as ML detector.     

Reduced-Complexity Turbo Equalization for Turbo Coded MIMO/OFDM Systems

1IntroductionTowards wireless systems Beyondthe3G(B3G),it isa great challenge for the physical layer to support high-speed transmissioninthe mobile environment to providecomfortable Internet access.Multiple Input MultipleOutput(MI MO)technique is effectiv…     

Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection

This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multipleinput and multiple-output (MIMO) channels. The proposed MCMC detector (Log-MAP-tb b-MCMC) operates in a strictly bit-wise fashion and adopts Log-MAP algorithm with table look-up. When concatenated with an optimized low-density parity-check (LDPC) code, Log-MAP-tb b-MCMC can operate within 1.2-1.8 dB of the capacity of MIMO systems with 8 transmit/receive antennas at spectral efficiencies up to n = 24 bits/channel use (b/ch). This result improves upon best performance achieved by turbo coded systems using list sphere decoding (LSD) detector by 2.3-3.8 dB, leading to nearly 50% reduction in the capacity gap. Detailed comparisons of the Log- MAP-tb b-MCMC with LSD based detectors demonstrate that MCMC detector is indeed the detector of choice for achieving channel capacity both in terms of performance and complexity.     

Iterative multiuser detection/decoding for turbo coded CDMA systems

We propose a novel scheme for iterative multiuser detection and turbo decoding. The multiuser detector and single-user turbo decoders are coupled such that after each turbo decoding iteration the extrinsic information of the interfering users is passed to the multiuser detector, and after each multiuser iteration, updated a posteriori probabilities are passed to the single-user turbo decoders as the soft input metrics. In synchronous systems, the proposed detector approaches the multiuser capacity limit within 1 dB in the low signal-to-noise ratio region     

Energy efficient virtual MIMO communication for wireless sensor networks

Virtual multiple input multiple output (MIMO) techniques are used for energy efficient communication in wireless sensor networks. In this paper, we propose energy efficient routing based on virtual MIMO. We investigate virtual MIMO for both fixed and variable rates. We use a cluster based virtual MIMO cognitive model with the aim of changing operational parameters (constellation size) to provide energy efficient communication. We determine the routing path based on the virtual MIMO communication cost to delay the first node death. For larger distances, the simulation results show that virtual MIMO (2×2) based routing is more energy efficient than SISO (single input single output) and other MIMO variations.