On vector perturbation precoding for the MIMO Gaussian broadcast channel

Avner, Yuval; Zaidel, Benjamin M.; Shamai, Shlomo

doi:10.1109/isit.2011.6033842

Cited by 5 publications

(3 citation statements)

References 39 publications

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“…We assume that the lattice Λ u is a good lattice and the user data vectors {u k,b (x) ∀k, b, x} are independent and they are uniformly distributed over V u . The main idea behind TDVP [12] is to relax the user data vectors u k,b (x) ∀k, b, x into the lattice Λ u by adding a lattice point to them such that the average power is minimized at each transmitter in a sequential fashion. Let v k,b (x) denote the beamforming vector for user k at location x + b : x ∈ X which is employed at BS b.…”

Section: A Channel Statistics and Estimationmentioning

confidence: 99%

“…Lemma 2: [12] Suppose x of the average power P x is uniformly distributed over the lattice Λ of dimension n, which is a good lattice for quantization and z is an independent noise vector with the average power P n . If we have the inputoutput relation y = [x + z] mod Λ, then the following rate is achievable…”

Section: Achievable Ratesmentioning

confidence: 99%

“…However, these works assume that CSI is perfectly available at the transmitter or otherwise give upper and lower bounds on the sum rate. Avner et al [12] proposed a VP technique operating in time domain, called time domain VP (TDVP), where the data vector for each user is perturbed in time domain instead of user domain. In this paper, we investigate the performance of TDVP in a largesize system.…”

Section: Introductionmentioning

confidence: 99%

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Massive MIMO With Nonlinear Precoding: Large-System Analysis

Mazrouei-Sebdani¹,

Krzymien²,

Melzer³

2016

IEEE Trans. Veh. Technol.

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In this paper, we consider time domain vector perturbation (TDVP) in a large-system limit when channel state information (CSI) is imperfect due to pilot contamination and we derive the system's achievable sum rate per cell. We use random matrix methods to avoid time-consuming MonteCarlo simulations. Numerical results show that in general linear precoding ensures higher sum rate than time domain vector perturbation in the massive MIMO regime. Index Terms-Massive MIMO, large-system analysis, time domain vector perturbation (TDVP). I. INTRODUCTIONIn a Gaussian MIMO broadcast channel it has been proved that dirty paper coding (DPC) [1]-[3], which is a very complex non-linear precoding technique, delivers the entire capacity region and achieves the sum capacity [2]-[4]. There exist other non-linear techniques of lower complexity but suboptimal, such as Tomlinson-Harashima precoding (THP) [5], [6] and vector perturbation (VP) [7]. Analysis of non-linear techniques employing VP is much more complicated than that of linear techniques because perturbing vectors are highly correlated and data-dependent. Adding to that, imperfect CSI and user scheduling make the analysis even harder [8]. There are several publications, which attempt to examine analytically the behavior of VP techniques [9]-[11]. However, these works assume that CSI is perfectly available at the transmitter or otherwise give upper and lower bounds on the sum rate. Avner et al. [12] proposed a VP technique operating in time domain, called time domain VP (TDVP), where the data vector for each user is perturbed in time domain instead of user domain. In this paper, we investigate the performance of TDVP in a largesize system. We use the framework developed in [13]-[15] and random matrix theory [16] to avoid time-consuming MonteCarlo simulations and get better insight into the problem.

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Section: A Channel Statistics and Estimationmentioning

confidence: 99%

Section: Achievable Ratesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Massive MIMO With Nonlinear Precoding: Large-System Analysis

Mazrouei-Sebdani¹,

Krzymien²,

Melzer³

2016

IEEE Trans. Veh. Technol.

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Far-End Crosstalk Mitigation for Future Wireline Networks Beyond G.mgfast: A Survey and an Outlook

Zhang

et al. 2020

IEEE Access

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With the escalating demand for high speed, high reliability, low latency, low cost and ubiquitous connectivity, the telecommunications industry is entering a new era where the ultimate optimality of the current wireline-wireless access network has to be achieved. Regarding the current wireline network paradigm, dominated by the copper-based digital subscriber lines (DSL) technology, multi-Gigabit data rate is the ambitious design objective at the customer end for the forthcoming ITU-T G.mgfast standard. In order to prepare for the new challenges in the era of total network convergence, both the wireline and the wireless community must be able to think beyond their respective conventions and learn from each other if necessary. Overall, the current DSL-based wireline network architecture is prone to the mutual interference resulting in far-end crosstalk (FEXT). The newly expanded 424/848 MHz spectrum of the ambitious G.mgfast project introduces far higher FEXT than that over the current 212/30 MHz G.fast/VDSL2 band. Additionally, the coexistence of multiple standards will also cause 'alien' FEXT. In these cases, using the plain zero forcing precoding (ZFP) will no longer attain a sufficiently high performance. However, as shown in the field of wireless communications, using lattice reduction as a signal space remapping technique significantly improves the performance of traditional multiuser detectors (MUD) and of the respective multiuser precoders (MUP). These promising techniques have largely remained unexploited in commercial wireless communications, due to their complexity in the face of the rapidly fluctuating wireless channels. In this survey, we present an overview of the state-of-the-art in wireline access network and an outlook for recent technological advances in the holistic 'wireline + wireless' access network in the context of network convergence, focusing on the dominant challenge of FEXT mitigation in future DSL networks. Against this background, we investigate both the family of linear precoding and of the Tomlinson-Harashima precoding (THP) schemes conceived for classic DSL. Furthermore, we present a tutorial on the family of lattice reduction aided MUPs, as well as quantifying their expected performances in realistic DSL scenarios. As a by-product, we also demonstrate the duality between MUP and MUD, in the hope that the fifty years' history of MUD could be used to accelerate the development of efficient near-optimal MUPs for future DSL. Under the recommended operating conditions of the 212 MHz profile of G.fast, our benchmark comparisons indicate that the lattice reduction aided techniques are very powerful compared to conventional schemes. In particular, their good performances do not rely on optimized spectrum balancing, and they are also shown to be relatively robust against channel state information (CSI) estimation error, under the assumption of perfectly time-invariant DSL channels.

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On vector perturbation precoding for the MIMO Gaussian broadcast channel

Avner

Zaidel

Shamai

2011

2011 IEEE International Symposium on Information Theory Proceedings

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Precoding schemes in the framework of vector perturbation (VP) for the multiple-input multiple-output (MIMO) Gaussian broadcast channel (GBC) are investigated. The VP scheme, originally a "one-shot" technique, is generalized to encompass processing over multiple time instances. Using latticebased extended alphabets ("perturbations"), and considering the infinite time-span extension limit, a lower bound on the achievable sum-rate using the generalized VP scheme is analytically obtained, by which it is shown to achieve the optimum sum-rate in the high signal-to-noise ratio (SNR) regime (both in terms of degrees-of-freedom and power offset). The above lower bound is constructively obtained by means of an efficient practically oriented suboptimum transmit energy minimization algorithm, which has merits of its own, and it demonstrates the significant performance enhancement that can be obtained by preprocessing over multiple symbol instances, potentially eliminating the gap to the ultimate performance at high SNRs. For the 2 × 2 MIMO GBC, the VP scheme is generalized further, and an inner bound for the entire achievable rate region is obtained, by which an interesting correspondence is identified to the ultimate capacity region, as obtained by "dirty paper" coding (DPC).

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On vector perturbation precoding for the MIMO Gaussian broadcast channel

Cited by 5 publications

References 39 publications

Massive MIMO With Nonlinear Precoding: Large-System Analysis

Massive MIMO With Nonlinear Precoding: Large-System Analysis

Far-End Crosstalk Mitigation for Future Wireline Networks Beyond G.mgfast: A Survey and an Outlook

On vector perturbation precoding for the MIMO Gaussian broadcast channel

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