Optimal channel assignment with aggregation in multi-channel systems: A resilient approach to adjacent-channel interference

Uyanık, Gülnur Selda; Abdel-Rahman, Mohammad J.; Krunz, Marwan

doi:10.1016/j.adhoc.2014.03.007

Cited by 19 publications

(7 citation statements)

References 32 publications

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“…Lemma 3: Given the subcarrier and user , there are at least two users such that (20) Proof: Let us define users and , then applying rule (3) to yields (21) By definition it is and , so that we can write (22) where the equality relation holds only if . By defining and , replacing (22) in (21) yields (23) Hence, by means of Lemma 3 we can find users and such that and so that in inequality (19) can be bounded as (24) Thus, since it is , inequality (24) yields (25) and since it is Since contraction mappings have a unique fixed point to which the mapping converges for any initial vector, we can conclude that ReMP converges to a unique vector regardless of the choice of the initial messages.…”

Section: A Convergencementioning

confidence: 99%

“…The assignment problem can be formulated as a linear integer programming problem (1) where the binary assignment variable is one when resource is assigned to user and zero otherwise, and must hold for feasibility. Problem (1) can be interpreted as a cell-based optimization problem [23] for an OFDMA wireless systems, where nodes represent the users, nodes the available channels, the number of requested channels, e.g., the subcarriers in an OFDMA system, and the power budget for user to utilise resource .…”

Section: Resource Assignment Problemmentioning

confidence: 99%

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On the Convergence and Optimality of Reweighted Message Passing for Channel Assignment Problems

Moretti

Abrardo

Belleschi

2014

IEEE Signal Process. Lett.

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Many assignment problems, and channel allocation\ud in OFDMA networks is a typical example, can be formulated as\ud bipartite weighted b-matching (BWBM) problems. In this letter\ud we provide a proof of the convergence and the optimality of the\ud reweighted message passing (ReMP) algorithm when applied to\ud solve BWBM problems in a distributed fashion. To this aim, we\ud first show that the ReMP rule is a contraction mapping under\ud a maximum mapping norm. Then, we show that the fixed convergence\ud point is an optimal solution for the original assignment\ud problem

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Section: A Convergencementioning

confidence: 99%

Section: Resource Assignment Problemmentioning

confidence: 99%

On the Convergence and Optimality of Reweighted Message Passing for Channel Assignment Problems

Moretti

Abrardo

Belleschi

2014

IEEE Signal Process. Lett.

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“…Two joint powerchannel allocation schemes (CAD-MAC) have been presented by [87] which perform channel aggregation to increase the data transmission rate along with optimizing energy efficiency of cognitive ad hoc networks. Another channel assignment scheme has been proposed for channel aggregation in multichannel systems [86] which maximizes the spectrum efficiency by minimizing the size of guard band required to establish a new link. The concept of channel aggregation has been elaborated by [29] in which multiple radio access technologies (RATs) can be combined to form a high speed logical channel.…”

Section: ) Channel Aggregationmentioning

confidence: 99%

A Survey of Channel Bonding for Wireless Networks and Guidelines of Channel Bonding for Futuristic Cognitive Radio Sensor Networks

Bukhari

Rehmani

Siraj

2016

IEEE Commun. Surv. Tutorials

132

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Abstract-Channel bonding (CB) is a proven technique to increase bandwidth and reduce delays in wireless networks. It has been applied in traditional wireless networks such as cellular networks and wireless local area networks along with the emerging cognitive radio networks. This paper first focuses on providing a survey of CB schemes for traditional wireless networks such as cellular networks, wireless local area networks and wireless sensor networks, and then provides a detailed discussion on the CB schemes proposed for cognitive radio networks. Finally, we highlight a number of issues and challenges regarding CB in cognitive radio sensor networks and also provide some guidelines on using CB schemes in these futuristic networks.

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“…Our objective in this paper is to design GBA channel assignment schemes for DSA networks, where channel quality is uncertain. It has been shown in [19], [20] that to attain optimal spectrum efficiency, channels need to be assigned on a per-block basis (as will be explained in Section II). Given this, the channel assignment problem in [19] can be restated as follows: Given the set of idle frequency blocks, obtain a combination of idle frequency blocks that either satisfies the link demand or achieves the nearest rate to this demand.…”

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confidence: 99%

Stochastic Guard-Band-Aware Channel Assignment With Bonding and Aggregation for DSA Networks

Abdel-Rahman

Krunz

2015

IEEE Trans. Wireless Commun.

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Fading and shadowing along with the primary user dynamics make channel quality in dynamic spectrum access networks uncertain. Furthermore, the imperfect design of filters and amplifiers in wireless devices motivates the need for guard-bands (GBs) to prevent adjacent-channel interference. In this paper, we develop novel stochastic GB-aware sequential and batch channel assignment schemes that aim at maximizing the spectrum efficiency. In line with recent IEEE 802.11 and LTE standards, our schemes support bonding and aggregation. We propose two assignment models for each of the sequential and batch schemes: a static single-stage and an adaptive two-stage. In the static model, channel assignment is performed once such that the rate demands are probabilistically met. The adaptive model is a two-stage model, where the initial assignment may be corrected once uncertainties are partially revealed. We refer to our formulations of the sequential and batch static assignments as chance-constrained stochastic subset-sum problem (CSSP) and chance-constrained stochastic multiple subset-sum problem (CMSSP), respectively. Moreover, we develop stochastic formulations for the sequential and batch adaptive assignments, which we refer to as two-stage CSSP with recourse (CSSPR) and two-stage CMSSP with recourse (CMSSPR), respectively. Finally, we present computationally efficient simplified versions of CSSP and CSSPR with near-optimal performance. Index Terms-Channel assignment, dynamic spectrum access, guard bands, multiple subset-sum problem, spectrum efficiency, stochastic optimization.

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Optimal channel assignment with aggregation in multi-channel systems: A resilient approach to adjacent-channel interference

Cited by 19 publications

References 32 publications

On the Convergence and Optimality of Reweighted Message Passing for Channel Assignment Problems

On the Convergence and Optimality of Reweighted Message Passing for Channel Assignment Problems

A Survey of Channel Bonding for Wireless Networks and Guidelines of Channel Bonding for Futuristic Cognitive Radio Sensor Networks

Stochastic Guard-Band-Aware Channel Assignment With Bonding and Aggregation for DSA Networks

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