A low-complexity channel shortening receiver with diversity support for evolved 2G devices

Hu, Sha; Kroll, Harald; Huang, Qiuting; Rusek, Fredrik

doi:10.1109/icc.2016.7511498

Cited by 10 publications

(13 citation statements)

References 13 publications

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“…WithĈ defined in (12) and (13), respectively, the number of independent signal dimensions ρ is calculated as the pre-log factor, i.e., the high signal-to-noise ratio (SNR) slope ofĈ,…”

Section: Independent Signal Dimensions With the Lismentioning

confidence: 99%

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Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces

Rusek

Edfors

2018

IEEE Trans. Signal Process.

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812

568

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In this paper, we consider the potential of data-transmission in a system with a massive number of radiating and sensing elements, thought of as a contiguous surface of electromagnetically active material. We refer to this as a large intelligent surface (LIS). The "LIS" is a newly proposed concept, which conceptually goes beyond contemporary massive MIMO technology, that arises from our vision of a future where man-made structures are electronically active with integrated electronics and wireless communication making the entire environment "intelligent".We firstly consider capacities of single-antenna autonomous terminals communicating to the LIS where the entire surface is used as a receiving antenna array. Under the condition that the surfacearea is sufficiently large, the received signal after a matched-filtering (MF) operation can be closely approximated by a sinc-function-like intersymbol interference (ISI) channel. Secondly, we analyze the capacity per square meter (m 2 ) deployed surface,Ĉ, that is achievable for a fixed transmit power per volume-unit,P ; the volume-unit can be m, m 2 , and m 3 depending on the scenario under investigation. As terminal-density increases, the limit ofĈ achieved when the wavelength λ approaches zero isP /(2N 0 )[nats/s/Hz/volume-unit], where N 0 is the spatial power spectral density (PSD) of the additive white Gaussian noise (AWGN). Moreover, we also show that the number of independent signal dimensions per m deployed surface is 2/λ for one-dimensional terminal-deployment, and π/λ 2 per m 2 for two and three dimensional terminal-deployments. Thirdly, we consider implementations of the LIS in the form of a grid of conventional antenna elements and show that, the sampling lattice that minimizes the surface-area of the LIS and simultaneously obtains one signal space dimension for every spent antenna is the hexagonal lattice. Lastly, we extensively discuss the design of the state-of-the-art low-complexity channel shortening (CS) demodulator for data-transmission with the LIS.The authors are with the P 2N 0 [nats/s/Hz/volume-unit], whereP is the transmit power per volume-unit and N 0 is the spatial power spectral density (PSD) of additive white Gaussian noise (AWGN). In particular, we show

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“…WithĈ defined in (12) and (13), respectively, the number of independent signal dimensions ρ is calculated as the pre-log factor, i.e., the high signal-to-noise ratio (SNR) slope ofĈ,…”

Section: Independent Signal Dimensions With the Lismentioning

confidence: 99%

“…Under the two extreme cases ν = 0 and ν = K−1, as shown in [12], [13] the CS demodulator is identical to the LMMSE and BCJR demodulators, respectively. The Ungerboeck model based branch metric in the BCJR algorithm of the CS demodulator is computed as…”

Section: Channel Shortening Demodulator Design For Data-transmissimentioning

confidence: 99%

Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces

Rusek

Edfors

2018

IEEE Trans. Signal Process.

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812

568

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“…As will be explained later, the UBM shortener can not be extended by decision-feedback using the methods introduced in [1], [15], [20]. Instead we show that we can overcome the performance losses of the UBM by applying the information 1 In relation to higher-order modulations and code-rates, which require high SNRs to decode. theoretical MILB approach to the Forney model instead of the Ungerboeck model.…”

mentioning

confidence: 89%

“…As there is no feedback filter, with the UBM shortener there is no decision-feedback process in the RS-SOVE. In [1], [20], the UBM shortener was successfully implemented for GSM/EDGE systems, and showed superior detection performance, yet with a much lower complexity than the HOM shortener. However, as shown in [20], in the high signal-to-noise (SNR) regime 1 , the UBM shortener suffers from performance losses and renders a bit-error-rate (BER) error floor.…”

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confidence: 99%

Optimal Channel Shortener Design for Reduced- State Soft-Output Viterbi Equalizer in Single-Carrier Systems

Hu¹,

Kroll²,

Huang³

et al. 2017

IEEE Trans. Commun.

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We consider optimal channel shortener design for reduced-state soft-output Viterbi equalizer (RS-SOVE) in single-carrier (SC) systems. To use RS-SOVE, three receiver filters need to be designed: a prefilter, a target response and a feedback filter. The collection of these three filters are commonly referred to as the "channel shortener". Conventionally, the channel shortener is designed to transform an intersymbol interference (ISI) channel into an equivalent minimum-phase equivalent form. In this paper, we design the channel shortener to maximize a mutual information lower bound (MILB) based on a mismatched detection model. By taking the decision-feedback quality in the RS-SOVE into consideration, the prefilter and feedback filter are found in closed forms, while the target response is optimized via a gradient-ascending approach with the gradient explicitly derived. The information theoretical properties of the proposed channel shortener are analyzed. Moreover, we show through numerical results that, the proposed channel shortener design achieves superior detection performance compared to previous channel shortener designs at medium and high code-rates.

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“…In the emerging Internet of things (IoT) [1] and device-to-device (D2D) [2] communication systems, a transmit node equipped with M transmit antennas may broadcast messages simultaneously to N low-cost receive nodes that are equipped with a single antenna. Under the assumption that the number of transmit antennas are much larger than the number of served users, i.e.,…”

Section: Introductionmentioning

confidence: 99%

A Generalized Zero-Forcing Precoder With Successive Dirty-Paper Coding in MISO Broadcast Channels

Rusek

2017

IEEE Trans. Wireless Commun.

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In this paper, we consider precoder designs for multiuser multiple-input-single-output (MISO) broadcasting channels. Instead of using a traditional linear zero-forcing (ZF) precoder, we propose a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for datatransmissions, namely, the GZF-DP precoder, where the suffix 'DP' stands for 'dirty-paper'. The GZF-DP precoder is designed to generate a band-shaped and lower-triangular effective channel F such that only the entries along the main diagonal and the ν first lower-diagonals can take non-zero values.Utilizing the successive DPC, the known non-causal inter-user interferences from the other (up to) ν users are canceled through successive encoding. We analyze optimal GZF-DP precoder designs both for sum-rate and minimum user-rate maximizations. Utilizing Lagrange multipliers, the optimal precoders for both cases are solved in closed-forms in relation to optimal power allocations. For the sum-rate maximization, the optimal power allocation can be found through water-filling, but with modified waterlevels depending on the parameter ν. While for the minimum user-rate maximization that measures the quality of the service (QoS), the optimal power allocation is directly solved in closed-form which also depends on ν. Moreover, we propose two low-complexity user-ordering algorithms for the GZF-DP precoder designs for both maximizations, respectively. We show through numerical results that, the proposed GZF-DP precoder with a small ν (≤ 3) renders significant rate increments compared to the previous precoder designs such as the linear ZF and user-grouping based DPC (UG-DP) precoders. Index TermsPrecoder design, zero-forcing (ZF), dirty-paper coding (DPC), broadcasting channel, multi-user, multiple-input-single-output (MISO), inter-user interference, water-filling, sum-rate maximization, minimum user-rate maximization, user-ordering.The authors are with the

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A low-complexity channel shortening receiver with diversity support for evolved 2G devices

Cited by 10 publications

References 13 publications

Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces

Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces

Optimal Channel Shortener Design for Reduced- State Soft-Output Viterbi Equalizer in Single-Carrier Systems

A Generalized Zero-Forcing Precoder With Successive Dirty-Paper Coding in MISO Broadcast Channels

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