Widely linear MMSE receivers for linear dispersion space-time block-codes

The use of proper, i.e., circularly symmetric, complex Gaussian signals for all users is known to be optimal in broadcast channels with proper complex Gaussian noise from an information theoretic point of view, i.e., they are employed in the capacityachieving strategy. However, such proper per-user transmit signals are not necessarily optimal for problems with quality-of-service (QoS) constraints if the transmit strategy is restricted to widely linear transceivers without time-sharing. This is shown by deriving the QoS feasibility region of the multiple-input multiple-output broadcast channel with improper Gaussian per-user transmit signals and widely linear transceivers.Index Terms-Asymmetric complex signaling, broadcast channels, improper signals, multiuser MIMO systems, quality-of-service (QoS) region, widely linear transceivers.

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“…1) due to the new factor of 2 in the exponent. However, for any , we have that (20) as can be seen in Fig. 1.…”

Section: Qos Feasibility Region Of Mimo Bcs With Improper Transmimentioning

confidence: 92%

“…Due to (20), the feasibility region for proper transmit signals is a subset of the one for improper transmit signals. This does not imply a statement about the transmit power required to fulfill the rate requirements (for this question, cf.…”

Section: Qos Feasibility Region Of Mimo Bcs With Improper Transmimentioning

confidence: 99%

QoS Feasibility in MIMO Broadcast Channels With Widely Linear Transceivers

Joham

Utschick

2013

IEEE Signal Process. Lett.

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“…Communication systems with asymmetric transmission and/or improper noise require appropriate treatment in terms of equalization, estimation, filtering and detection to account for the induced improperness. Therefore, WL processing models are incorporated to design several estimation [6], filtering [31], and detection [277] algorithms. WL processing is utilized in communication systems that apply asymmetric constellations e.g., [48], [256], [278]- [280] , and/or encounter improper noise, e.g., [45].…”

Section: B Asymmetric Signal Recoverymentioning

confidence: 99%

“…WL processing is utilized in communication systems that apply asymmetric constellations e.g., [48], [256], [278]- [280] , and/or encounter improper noise, e.g., [45]. Additionally, it is exploited in lineardispersion STBC, e.g., [277], [281], [282], and, recently, in IC and BC [73], [82]. 1) Equalization: In band-limited, high data rate digital communication systems, equalizers flatten the channel frequency response in order to minimize channel distortion on the transmitted information symbols.…”

Section: B Asymmetric Signal Recoverymentioning

confidence: 99%

A Journey From Improper Gaussian Signaling to Asymmetric Signaling

Javed

Amin

Shihada

et al. 2020

IEEE Commun. Surv. Tutorials

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The deviation of continuous and discrete complex random variables from the traditional proper and symmetric assumption to a generalized improper and asymmetric characterization (accounting correlation between a random entity and its complex conjugate), respectively, introduces new design freedom and various potential merits. As such, the theory of impropriety has vast applications in medicine, geology, acoustics, optics, image and pattern recognition, computer vision, and other numerous research fields with our main focus on the communication systems. The journey begins from the design of improper Gaussian signaling in the interference-limited communications and leads to a more elaborate and practically feasible asymmetric discrete modulation design. Such asymmetric shaping bridges the gap between theoretically and practically achievable limits with sophisticated transceiver and detection schemes in both coded/uncoded wireless/optical communication systems. Interestingly, introducing asymmetry and adjusting the transmission parameters according to some design criterion render optimal performance without affecting the bandwidth or power requirements of the systems. This dual-flavored article initially presents the tutorial base content covering the interplay of reality/complexity, propriety/impropriety and circularity/non-circularity and then surveys majority of the contributions in this enormous journey.

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“…For an improper signal, the processing model should depend on both the signal itself and its complex conjugate. Such a methodology is referred to as widely-linear processing [14]- [16] and has been utilized to develop several estimation [17], filtering [18], and detection [19] algorithms.…”

Section: Introductionmentioning

confidence: 99%

Complex-Valued Gaussian Sum Filter for Nonlinear Filtering of Non-Gaussian/Non-Circular Noise

Mohammadi

Plataniotis

2015

IEEE Signal Process. Lett.

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Motivated by application of Gaussian sum filters (GSF) and multiple model adaptive estimation (MMAE) approaches in scenarios where assumption of proper (circular) Gaussian signals is not valid, the letter proposes a novel complexvalued Gaussian sum filter (C/GSF) for non-linear filtering of non-Gaussian/non-circular measurement noise. Although the literature on recursive state estimation using GSF is rich, its complex-valued counterpart which incorporates the full second-order statistics of the system and can cope with nonGaussian/non-circular measurements, has not yet been investigated in the literature. The paper addresses this gap. The C/GSF is a computationally attractive adaptive filter where the number of non-circular Gaussian components is controlled utilizing a modified Bayesian learning technique which is used to collapse the resulting non-Gaussian sum mixture into an equivalent complex-valued Gaussian term. Simulation results indicate that the C/GSF provides significant performance improvement over its traditional counterparts.

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Widely linear MMSE receivers for linear dispersion space-time block-codes

Cited by 22 publications

References 63 publications

QoS Feasibility in MIMO Broadcast Channels With Widely Linear Transceivers

QoS Feasibility in MIMO Broadcast Channels With Widely Linear Transceivers

A Journey From Improper Gaussian Signaling to Asymmetric Signaling

Complex-Valued Gaussian Sum Filter for Nonlinear Filtering of Non-Gaussian/Non-Circular Noise

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