Joint power control and intracell scheduling of DS-CDMA nonreal time data

Berggren, Fredrik; Kim, Seong-Lyun; Jäntti, Riku; Zander, Jens

doi:10.1109/49.957302

Cited by 87 publications

(67 citation statements)

References 13 publications

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“…The transmit power vector can be obtained by solving the following linear inequalities: (6) with constraint (7) where is the maximum transmit power at the BS. The condition for a feasible power vector allocation is [9] (8)…”

Section: Packet Scheduling With Power Allocationmentioning

confidence: 99%

Quality-of-service provisioning and efficient resource utilization in CDMA cellular communications

Jiang

Zhuang

Shen

et al. 2006

IEEE J. Select. Areas Commun.

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Abstract-One of the major challenges in supporting multimedia services over Internet protocol (IP)-based code-division multiple-access (CDMA) wireless networks is the quality-of-service (QoS) provisioning with efficient resource utilization. Compared with the circuit-switched voice service in the second-generation CDMA systems (i.e., IS-95), heterogeneous multimedia applications in future IP-based CDMA networks require more complex QoS provisioning and more sophisticated management of the scarce radio resources. This paper provides an overview of the CDMA-related QoS provisioning techniques in the avenues of packet scheduling, power allocation, and network coordination, summarizes state-of-the-art research results, and identifies further research issues.Index Terms-Code-division multiple-access (CDMA), intercell coordination, multimedia services, packet scheduling, power allocation, quality-of-service (QoS), soft handoff.

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Section: Packet Scheduling With Power Allocationmentioning

confidence: 99%

Quality-of-service provisioning and efficient resource utilization in CDMA cellular communications

Jiang

Zhuang

Shen

et al. 2006

IEEE J. Select. Areas Commun.

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“…The above parameters are used for a) the admission control mechanism, [15]- [19], and b) the power control mechanism, [20] [21]. In the first case, the admission of a new call or a handover depends on the interference it would have caused if accepted.…”

Section: • Uplink Power Target Ievel Per Pixel and Service P:;es (Ps)mentioning

confidence: 99%

Efficient Location-Based Hard Handoff Algorithms for Cellular Systems

Markopoulos

Pissaris

Kyriazakos

et al. 2004

Lecture Notes in Computer Science

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Abstract. Mobile world's rapid growth hasspurred development of new protocols and new algorithms to meet changing operation requirements-such as mobile networking, and quality-of-service support. Handoff is one of the most critical procedures in cellular systems. Network operators give emphasis to optimize handover, since it is strongly related to dropped calls, network overload and subsequently users' criticism. Handoff can be seen as a blind procedure, if it is only based on the comparison of measurements, without the information of location. Since signal propagation and pathloss are complex in nature, we can expect unnecessary and wrong handoff executions. Both UMTS and those of the second generation (GSM) systems will require redefined handoff algorithms of active connections as the smooth mobility support and continuous connection are essential issues for obtaining high performance and increasing user satisfaction. In this paper we present a set of intelligent algorithms using the mobile terminal (MT) location information and area awareness to assist safe handoff decisions. The implemented algorithms are validated by means of cellular network simulators that clearly show the impact of these techniques to major system performance metrics.

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“…We consider two link adaptation functions commonly used in the literature -linear and logarithmic. A linear link adaptation mechanism adjusts the transmission rate in proportion to the SINR [14], [15], [16]. In this model which is appropriate for CDMA systems where data rate is primarily adjusted by a spreading factor, the transmission rate for link l is give by…”

Section: Link Adaptationmentioning

confidence: 99%

“…Then the new optimization problem is to minimize the total average power consumed during the QoS period and is stated as min π h(P avg ) subject to (14) and (15). (17) Note this optimization involves considering every possible policy.…”

Section: A Problem Formulation : Primal Problemmentioning

confidence: 99%

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Downlink optimization of indoor wireless networks using multiple antenna systems

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-We compare the performance of two multiple antenna systems to be used in quality of service (QoS) supported indoor wireless networks. While a conventional array antenna system (AAS) has collocated, closely spaced antenna elements, a distributed antenna system (DAS) has largely spaced antennas over the entire area of radio coverage. To support multimedia applications requiring high bandwidth and on time delivery, we propose a set of highly spectrum efficient radio resource management algorithms. We focus on the optimization of downlink since many kinds of Internet traffic show the downlink dominance in their traffic asymmetry. To maximize the downlink throughput, we present a new transmit beamforming algorithm which can be equally applied to both DAS and AAS. The beamforming algorithm is integrated with a link scheduling algorithm that exploits the space division multiplexing (SDM) capability of multiple antenna systems to meet the QoS requirements of all terminals. Numerical examples conducted for a line of sight (LOS) environment demonstrate that a network with DAS outperforms one with AAS in terms of signal coverage and provides 40 -160% higher capacity.

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Joint power control and intracell scheduling of DS-CDMA nonreal time data

Cited by 87 publications

References 13 publications

Quality-of-service provisioning and efficient resource utilization in CDMA cellular communications

Quality-of-service provisioning and efficient resource utilization in CDMA cellular communications

Efficient Location-Based Hard Handoff Algorithms for Cellular Systems

Downlink optimization of indoor wireless networks using multiple antenna systems

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