Bandwidth Balancing in Multi-Channel IEEE 802.16 Wireless Mesh Networks

Cicconetti, Claudio; Akyildiz, Ian F.; Lenzini, Luciano

doi:10.1109/infcom.2007.244

Cited by 51 publications

(57 citation statements)

References 17 publications

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“…, , = 10 log 10 Modulation method Number of bits 5 where is the background noise level. , is the strength of the signal sent by node and received by node , and it is given by the following equation:…”

Section: Sinr Model For Evaluating Transmission Qualitymentioning

confidence: 99%

Multiple regression analysis of IEEE 802.16j relay network throughput

Higo

Hasegawa

Taniguchi

et al. 2014

16th International Conference on Advanced Communication Technology

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Abstract-In IEEE 802.16j relay networks, time division multiple access (TDMA) is adopted for sharing wireless network resources while avoiding radio wave interference. Time slot assignment determines the degree of spatial reuse of wireless network resources and radio interference strength, which affects network performance. The relay network performance is also influenced by various factors, such as background noise level, path loss exponent, density of relay nodes, and transmission signal strength. In this paper, we present the results of multiple regression analysis of IEEE 802.16j relay network throughput. We first summarize the network environment parameters that affect the throughput of relay networks and conduct extensive simulation experiments with various sets of parameter values. From the simulation results, we investigate the relative effect of parameters on throughput performance by multiple regression analysis. The analysis results show that background noise level and path loss exponent are the key parameters for determining relay network throughput. We also obtain a regression equation to estimate the throughput with enough accuracy.

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Section: Sinr Model For Evaluating Transmission Qualitymentioning

confidence: 99%

Multiple regression analysis of IEEE 802.16j relay network throughput

Higo

Hasegawa

Taniguchi

et al. 2014

16th International Conference on Advanced Communication Technology

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“…In [13] we explained the FEBA procedure for requesting/ granting bandwidth in detail and gave a complete description of its data structures. In the following we explain the extended version of FEBA which supports differentiated services for traffic flows.…”

Section: B Request/grant Proceduresmentioning

confidence: 99%

FEBA: A Bandwidth Allocation Algorithm for Service Differentiation in IEEE 802.16 Mesh Networks

Cicconetti

Akyildiz

Lenzini

2009

IEEE/ACM Trans. Networking

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Abstract-In wireless mesh networks, the end-to-end throughput of traffic flows depends on the path length, i.e., the higher the number of hops, the lower becomes the throughput. In this paper, a fair end-to-end bandwidth allocation (FEBA) algorithm is introduced to solve this problem. FEBA is implemented at the medium access control (MAC) layer of single-radio, multiple channels IEEE 802.16 mesh nodes, operated in a distributed coordinated scheduling mode. FEBA negotiates bandwidth among neighbors to assign a fair share proportional to a specified weight to each end-to-end traffic flow. This way traffic flows are served in a differentiated manner, with higher priority traffic flows being allocated more bandwidth on the average than the lower priority traffic flows. In fact, a node requests/grants bandwidth from/to its neighbors in a round-robin fashion where the amount of service depends on both the load on its different links and the priority of currently active traffic flows. If multiple channels are available, they are all shared evenly in order to increase the network capacity due to frequency reuse. The performance of FEBA is evaluated by extensive simulations. It is shown that wireless resources are shared fairly among best-effort traffic flows, while multimedia streams are provided with a differentiated service that enables quality of service.

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“…There exist efficient ways to share hardware resources over multiple channels for those FIR filters. Meanwhile, cognitive radio (CR) exploits temporal and spatial variations of the spectrum in the radio environment [5,6]. CR improves spectrum efficiency by allocating different bandwidth per channel.…”

Section: Introductionmentioning

confidence: 99%

A low-cost FPGA implementation of multi-channel FIR filter with variable bandwidth

Park

2015

IEICE Electron. Express

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This paper proposes a low-cost implementation of a multichannel FIR filter on FPGA, where each channel can have variable bandwidth and coefficients. New structures of the tapped-delay line and the coefficient bank unit based on time-division multiplexing are proposed. Pipelined adder tree is used to expedite the filtering process without disturbing generation of control signals for multi-channel data access. From implementation results, it is found that the proposed 39-tap FIR filter involves 32% less number of slice registers as well as 65% less number of DSP blocks than the Xilinx FIR Core 5.0, and also supports variable bandwidth.

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Bandwidth Balancing in Multi-Channel IEEE 802.16 Wireless Mesh Networks

Cited by 51 publications

References 17 publications

Multiple regression analysis of IEEE 802.16j relay network throughput

Multiple regression analysis of IEEE 802.16j relay network throughput

FEBA: A Bandwidth Allocation Algorithm for Service Differentiation in IEEE 802.16 Mesh Networks

A low-cost FPGA implementation of multi-channel FIR filter with variable bandwidth

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