CTH06-6: Optimized Transmission for Upstream Vectored DSL Systems Using Zero-Forcing Generalized Decision-Feedback Equalizers

Chen, Chiang-Yu; Seong, Kibeom; Zhang, Rui; Cioffi, J.M.

doi:10.1109/glocom.2006.69

“…The main advantage of this method lies in that if the same computational routine can be simultaneously applied to all N subproblems, the overall computational time is maintained regardless of N . Other applications of the Lagrange dual-decomposition method for resource allocation in communication systems can be found in, e.g., [35]- [43].…”

Section: Multi-channel Transmissionmentioning

confidence: 99%

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

Zhang

¹

,

Liang

²

2008

IEEE J. Sel. Top. Signal Process.

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In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to trade off between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver.In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interferencepower constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission.Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multi-channel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well. Simulation results show that even under stringent interference-power constraints, substantial capacity gains are achievable for the secondary transmission by employing multi-antennas at the secondary transmitter. This is true even when the number of primary receivers exceeds that of secondary transmit antennas in a CR network, where an interesting "interference diversity" effect can be exploited. Index TermsCognitive radio (CR), opportunistic spectrum sharing, multiple-input multiple-output (MIMO), channel capacity, dynamic resource allocation, interference diversity, convex optimization.

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“…because otherwise, the optimal v that maximizes the Lagrangian in (42) will go unbounded to infinity, which contradicts the facts that the optimal value of the primal problem is bounded, and the duality gap is zero. Using (43), the dual problem in (41) can be expressed as (P5)…”

Section: A Miso Secondary User's Channelmentioning

confidence: 99%

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

Zhang,

Liang

2007

Preprint

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0

View full text Add to dashboard Cite

In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to trade off between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver.In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interferencepower constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission.Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multi-channel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well. Simulation results show that even under stringent interference-power constraints, substantial capacity gains are achievable for the secondary transmission by employing multi-antennas at the secondary transmitter. This is true even when the number of primary receivers exceeds that of secondary transmit antennas in a CR network, where an interesting "interference diversity" effect can be exploited.

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Signal Processing for Vectored Multichannel VDSL

Bergel

¹

,

Leshem

²

2014

Academic Press Library in Signal Processing: Volume 2 - Communications and Radar Signal Processing

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CTH06-6: Optimized Transmission for Upstream Vectored DSL Systems Using Zero-Forcing Generalized Decision-Feedback Equalizers

Cited by 9 publications

References 11 publications

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

Signal Processing for Vectored Multichannel VDSL

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