Turbo Receivers for Single User MIMO LTE-A Uplink

Berardinelli, Gilberto; Manchón, Carles Navarro; Deneire, Luc; Sørensen, Troels B.; Mogensen, Preben; Pajukoski, Kari

doi:10.1109/vetecs.2009.5073893

Cited by 24 publications

(19 citation statements)

References 7 publications

(11 reference statements)

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“…Nevertheless, none of these methods are directly applicable to SC-FDMA-based systems. For SC-FDMA, only a handful of non-linear data-detection methods exist [23][24][25]. While these methods achieve near-optimal performance in small-scale MIMO systems, their complexity does, similarly to tree-search-based methods, not scale well to large BS antenna arrays.…”

Section: Soft-output Data Detectionmentioning

confidence: 99%

Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection

Yin

et al. 2017

J Sign Process Syst

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Massive multi-user (MU) MIMO wireless technology promises improved spectral efficiency compared to that of traditional cellular systems. While datadetection algorithms that rely on linear equalization achieve near-optimal error-rate performance for massive MU-MIMO systems, they require the solution to large linear systems at high throughput and low latency, which results in excessively high receiver complexity. In this paper, we investigate a variety of exact and approximate equalization schemes that solve the system of linear equations either explicitly (requiring the computation of a matrix inverse) or implicitly (by directly computing the solution vector). We analyze the associated performance/complexity trade-offs, and we show that for small base-station (BS)-to-user-antenna ratios, exact and implicit data detection using the Cholesky decomposition achieves near-optimal performance at low complexity. In contrast, implicit data detection using approximate equalization methods results in the best trade-off for large BS-to-user-antenna ratios. By combining the advantages of exact, approximate, implicit, and explicit matrix inversion, we develop a new frequencyadaptive equalizer (FADE), which outperforms existing data-detection methods in terms of performance and complexity for wideband massive MU-MIMO systems.

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Section: Soft-output Data Detectionmentioning

confidence: 99%

Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection

Yin

et al. 2017

J Sign Process Syst

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“…In this manner, the disadvantaged CW has increased probability to be correctly decoded. For further details, we refer to [12]. This process can be repeated for a number of iterations.…”

Section: ) Linear Receiver: It Is Based On the Traditional Minimummentioning

confidence: 99%

Link Parameters Bundling across Multiple Component Carriers in LTE-A Uplink

Berardinelli

Sørensen

Mogensen

et al. 2010

2010 IEEE 71st Vehicular Technology Conference

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Abstract-A multiple component carrier (CC) solution has been agreed as the underlying structure of the Long Term Evolution -Advanced (LTE-A) systems, which are currently being standardized by the 3rd Generation Partnership Project (3GPP). In this deployment, the bundling of Modulation and Coding Scheme (MCS) and Hybrid Automatic Repeat Request (HARQ) parameters across multiple CCs is foreseen to maintain the feedback signaling comparable with the one of the previous LTE Release 8. This paper focuses on the transmission over multiple CCs in LTE-A Uplink. Issues related to the bundling of the link level parameters is discussed and a simple Codeword (CW) mixing strategy is proposed to boost the spectral efficiency performance while keeping low feedback overhead. Results show that, combined HARQ/MCS bundling can achieve the same performance of HARQ only bundling when used together with our proposed CW mixing strategy, with the advantage of a lower feedback overhead. CW mixing also leads to similar spectral efficiency when the bundling is performed over 2 and 3 CCs. The use of a turbo Successive Interference Cancellation (turbo SIC) receiver further improves the spectral efficiency, especially when antenna gain imbalance (AGI) occurs.

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“…In recent years, several schemes were proposed to perform interference cancellation in LTE downlink [3] and uplink [4][5][6][7][8][9][10]. However, few papers exist on low complexity implementation for software defined radio (SDR).…”

Section: Introductionmentioning

confidence: 99%

“…Thus, this scheme has many disadvantages for real time implementation. In papers [6][7][8][9][10], the log-likelihood ratios (LLR) from the channel decoder are sent back to the frequency domain to achieve interference cancellation. These schemes are similar to [5], but with an even longer feedback loop, which is from the channel decoder to the FDE.…”

Section: Introductionmentioning

confidence: 99%

LTE uplink MIMO receiver with low complexity interference cancellation

Yin

Cavallaro

2012

Analog Integr Circ Sig Process

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In LTE/LTE-A uplink receiver, frequency domain equalizers (FDE) are adopted to achieve good performance. However, in multi-tap channels, the residual inter-symbol and inter-antenna interference still exist after FDE and degrade the performance. Conventional interference cancellation schemes can minimize this interference by using frequency domain interference cancellation. However, those schemes have high complexity and large feedback latency, especially when adopting a large number of iterations. These result in low throughput and require a large amount of resource in software defined radio implementation. In this paper, we propose a novel low complexity interference cancellation scheme to minimize the residual interference in LTE/LTE-A uplink. Our proposed scheme can bring about 2 dB gains in different channels, but only adds up to 7.2 % complexity to the receiver. The scheme is further implemented on Xilinx FPGA. Compared to other conventional interference cancellation schemes, our scheme has less complexity, less data to store, and shorter feedback latency.

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Turbo Receivers for Single User MIMO LTE-A Uplink

Abstract: Abstract-TheThe turbo receiver's impact is however much reduced for both modulation schemes in a 2x4 configuration, due to the higher diversity gain provided by the additional receive antennas.

Cited by 24 publications

References 7 publications

Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection

Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection

Link Parameters Bundling across Multiple Component Carriers in LTE-A Uplink

LTE uplink MIMO receiver with low complexity interference cancellation

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