369 research outputs found

    VLSI Architectures and Rapid Prototyping Testbeds for Wireless Systems

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    The rapid evolution of wireless access is creating an ever changing variety of standards for indoor and outdoor environments. The real-time processing demands of wireless data rates in excess of 100 Mbps is a challenging problem for architecture design and verification. In this paper, we consider current trends in VLSI architecture and in rapid prototyping testbeds to evaluate these systems. The key phases in multi-standard system design and prototyping include: Algorithm Mapping to Parallel Architectures – based on the real-time data and sampling rate and the resulting area, time and power complexity; Configurable Mappings and Design Exploration – based on heterogeneous architectures consisting of DSP, programmable application-specific instruction (ASIP) processors, and co-processors; and Verification and Testbed Integration – based on prototype implementation on programmable devices and integration with RF units.Nokia Foundation FellowshipNokia CorporationNational InstrumentsNational Science Foundatio

    On the Achievable Rates of Decentralized Equalization in Massive MU-MIMO Systems

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    Massive multi-user (MU) multiple-input multiple-output (MIMO) promises significant gains in spectral efficiency compared to traditional, small-scale MIMO technology. Linear equalization algorithms, such as zero forcing (ZF) or minimum mean-square error (MMSE)-based methods, typically rely on centralized processing at the base station (BS), which results in (i) excessively high interconnect and chip input/output data rates, and (ii) high computational complexity. In this paper, we investigate the achievable rates of decentralized equalization that mitigates both of these issues. We consider two distinct BS architectures that partition the antenna array into clusters, each associated with independent radio-frequency chains and signal processing hardware, and the results of each cluster are fused in a feedforward network. For both architectures, we consider ZF, MMSE, and a novel, non-linear equalization algorithm that builds upon approximate message passing (AMP), and we theoretically analyze the achievable rates of these methods. Our results demonstrate that decentralized equalization with our AMP-based methods incurs no or only a negligible loss in terms of achievable rates compared to that of centralized solutions.Comment: Will be presented at the 2017 IEEE International Symposium on Information Theor

    LOW-COMPLEXITY AND HIGH-PERFORMANCE SOFT MIMO DETECTION BASED ON DISTRIBUTED M-ALGORITHM THROUGH TRELLIS-DIAGRAM

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    This paper presents a novel low-complexity multiple-input multipleoutput (MIMO) detection scheme using a distributed M-algorithm (DM) to achieve high performance soft MIMO detection. To reduce the searching complexity, we build a MIMO trellis graph and split the searching operations among different nodes, where each node will apply the M-algorithm. Instead of keeping a global candidate list as the traditional detector does, this algorithm keeps multiple small candidate lists to generate soft information. Since the DM algorithm can achieve good BER performance with a small M, the sorting cost of the DM algorithm is lower than that of the conventional K-best MIMO algorithm. The proposed algorithm is very suitable for high speed parallel processing.NokiaNokia Siemens Networks (NSN)XilinxNational Science Foundatio

    Scalable Architecture of MIMO Multi-carrier CDMA System on Programmable Logic

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    In this paper, a scalable architecture of the multicarrier CDMA system using Multiple-Input-Multiple-Output (MIMO) technology is designed in the programmable logic array. The system-level partitioning with different architecture design entries is described. The overall computing architecture for complex signal processing blocks, e.g., channel estimation, frequency domain equalization, demodulation etc is described. The MIMO architecture is easily extended from a SISO system with single antenna. This scalable architecture demonstrates resource utilization efficiency and easy extension to MIMO configurations

    Distributed Decoding in Cooperative Communications

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    In this paper, we present a novel relaying strategy called distributed and partial decoding. This strategy can be viewed as a variation of the decode and forward with the difference that the relay partially decodes the signal, re-transmits it to the destination, and the destination continues the decoding. By distributing the decoding process between the relay and the destination, the relay uses less processing power and less time. This is very suitable for practical applications in which relays are battery-operated (such as handsets) and do not want to use all their battery power on relaying the data of other users.Nokia CorporationNational Science Foundatio

    Soft Sphere Detection with Bounded Search for High-Throughput MIMO Receivers

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    We propose a soft sphere detection algorithm where search-bounds are determined based on the distribution of candidates found inside the sphere for different search levels. Detection accuracy of unbounded search is preserved while significant saving of memory space and reduction of latency is achieved. This probabilistic search algorithm provides significantly better frame-error rate performance than the soft K-best solution and has comparable performance and smaller computational complexity than the bounded depth-first search method. Techniques for efficient and flexible architecture design of soft sphere detectors are also presented. The estimated hardware cost is lower than the hardware cost of other soft sphere detectors from the literature, while high detection throughput per channel use is achieved

    UNIFIED DECODER ARCHITECTURE FOR LDPC/TURBO CODES

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    Low-density parity-check (LDPC) codes on par with convolutional turbo codes (CTC) are two of the most powerful error correction codes known to perform very close to the Shannon limit. However, their different code structures usually lead to different hardware implementations. In this paper, we propose a unified decoder architecture that is capable of decoding both LDPC and turbo codes with a limited hardware overhead. We employ maximum a posteriori (MAP) algorithm as a bridge between LDPC and turbo codes. We represent LDPC codes as parallel concatenated single parity check (PCSPC) codes and propose a group sub-trellis (GST) decoding algorithm for the efficient decoding of PCSPC codes. This algorithm achieves about 2X improvement in the convergence speed and is more numerically robust than the classical ”tanh” algorithm. What is more interesting is that we can generalize a unified trellis decoding algorithm for LDPC and turbo codes based on their trellis structures. We propose a reconfigurable computation kernel for log-MAP decoding of LDPC and turbo codes at a cost of ∼15% hardware overhead. Small lookup tables (LUTs) with 9 entries of 2-bit data are designed to implement the log-MAP algorithm. Fixed point (6:2) simulation results show that there is negligible or nearly no performance loss by using this LUT approximation compared to the ideal case. The proposed architecture results in scalable and flexible datapath units enabling parallel decoding of LDPC/turbo codes.NokiaNational Science Foundatio

    High Throughput VLSI Architecture for Soft-Output MIMO Detection Based on A Greedy Graph Algorithm

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    Maximum-likelihood (ML) decoding is a very computational- intensive task for multiple-input multiple-output (MIMO) wireless channel detection. This paper presents a new graph based algorithm to achieve near ML performance for soft MIMO detection. Instead of using the traditional tree search based structure, we represent the search space of the MIMO signals with a directed graph and a greedy algorithm is ap- plied to compute the a posteriori probability (APP) for each transmitted bit. The proposed detector has two advantages: 1) it keeps a fixed throughput and has a regular and parallel datapath structure which makes it amenable to high speed VLSI implementation, and 2) it attempts to maximize the a posteriori probability by making the locally optimum choice at each stage with the hope of finding the global minimum Euclidean distance for every transmitted bit x_k element of {-1, +1}. Compared to the soft K-best detector, the proposed solution significantly reduces the complexity because sorting is not required, while still maintaining good bit error rate (BER) performance. The proposed greedy detection algorithm has been designed and synthesized for a 4 x 4 16-QAM MIMO system in a TSMC 65 nm CMOS technology. The detector achieves a maximum throughput of 600 Mbps with a 0.79 mm2 core area.Nokia CorporationNational Science Foundatio
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