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Przemysław Pawełczak

Publications and source records attributed to Przemysław Pawełczak.

24 records · Page 2Linked to original sources

Impact of Connection Admission Process on the Direct Retry Load Balancing Algorithm in Cellular Network

We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks based on a new algorithm called direct retry with truncated offloading channel resource pool (DR$_{K}$). The model, developed for a baseline case of two cell network, differs in many respects from previous works on load balancing. Foremost, it incorporates the call admission process, through random access. In specific, the proposed model implements the Physical Random Access Channel used in 3GPP network standards. Furthermore, the proposed model allows the differentiation of users based on their priorities. The quantitative results illustrate that, for example, cellular network operators can control the manner in which traffic is offloaded between neighboring cells by simply adjusting the length of the random access phase. Our analysis also allows for the quantitative determination of the blocking probability individual users will experience given a specific length of random access phase. Furthermore, we observe that the improvement in blocking probability per shared channel for load balanced users using DR$_{K}$ is maximized at an intermediate number of shared channels, as opposed to the maximum number of these shared resources. This occurs because a balance is achieved between the number of users requesting connections and those that are already admitted to the network. We also present an extension of our analytical model to a multi-cell network (by means of an approximation) and an application of the proposed load balancing scheme in the context of opportunistic spectrum access.

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Throughput and Collision Analysis of Multi-Channel Multi-Stage Spectrum Sensing Algorithms

Multi-stage sensing is a novel concept that refers to a general class of spectrum sensing algorithms that divide the sensing process into a number of sequential stages. The number of sensing stages and the sensing technique per stage can be used to optimize performance with respect to secondary user throughput and the collision probability between primary and secondary users. So far, the impact of multi-stage sensing on network throughput and collision probability for a realistic network model is relatively unexplored. Therefore, we present the first analytical framework which enables performance evaluation of different multi-channel multi-stage spectrum sensing algorithms for Opportunistic Spectrum Access networks. The contribution of our work lies in studying the effect of the following parameters on performance: number of sensing stages, physical layer sensing techniques and durations per each stage, single and parallel channel sensing and access, number of available channels, primary and secondary user traffic, buffering of incoming secondary user traffic, as well as MAC layer sensing algorithms. Analyzed performance metrics include the average secondary user throughput and the average collision probability between primary and secondary users. Our results show that when the probability of primary user mis-detection is constrained, the performance of multi-stage sensing is, in most cases, superior to the single stage sensing counterpart. Besides, prolonged channel observation at the first stage of sensing decreases the collision probability considerably, while keeping the throughput at an acceptable level. Finally, in realistic primary user traffic scenarios, using two stages of sensing provides a good balance between secondary users throughput and collision probability while meeting successful detection constraints subjected by Opportunistic Spectrum Access communication.

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Analysis Framework for Opportunistic Spectrum OFDMA and its Application to the IEEE 802.22 Standard

We present an analytical model that enables throughput evaluation of Opportunistic Spectrum Orthogonal Frequency Division Multiple Access (OS-OFDMA) networks. The core feature of the model, based on a discrete time Markov chain, is the consideration of different channel and subchannel allocation strategies under different Primary and Secondary user types, traffic and priority levels. The analytical model also assesses the impact of different spectrum sensing strategies on the throughput of OS-OFDMA network. The analysis applies to the IEEE 802.22 standard, to evaluate the impact of two-stage spectrum sensing strategy and varying temporal activity of wireless microphones on the IEEE 802.22 throughput. Our study suggests that OS-OFDMA with subchannel notching and channel bonding could provide almost ten times higher throughput compared with the design without those options, when the activity and density of wireless microphones is very high. Furthermore, we confirm that OS-OFDMA implementation without subchannel notching, used in the IEEE 802.22, is able to support real-time and non-real-time quality of service classes, provided that wireless microphones temporal activity is moderate (with approximately one wireless microphone per 3,000 inhabitants with light urban population density and short duty cycles). Finally, two-stage spectrum sensing option improves OS-OFDMA throughput, provided that the length of spectrum sensing at every stage is optimized using our model.

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When Channel Bonding is Beneficial for Opportunistic Spectrum Access Networks

Transmission over multiple frequency bands combined into one logical channel speeds up data transfer for wireless networks. On the other hand, the allocation of multiple channels to a single user decreases the probability of finding a free logical channel for new connections, which may result in a network-wide throughput loss. While this relationship has been studied experimentally, especially in the WLAN configuration, little is known on how to analytically model such phenomena. With the advent of Opportunistic Spectrum Access (OSA) networks, it is even more important to understand the circumstances in which it is beneficial to bond channels occupied by primary users with dynamic duty cycle patterns. In this paper we propose an analytical framework which allows the investigation of the average channel throughput at the medium access control layer for OSA networks with channel bonding enabled. We show that channel bonding is generally beneficial, though the extent of the benefits depend on the features of the OSA network, including OSA network size and the total number of channels available for bonding. In addition, we show that performance benefits can be realized by adaptively changing the number of bonded channels depending on network conditions. Finally, we evaluate channel bonding considering physical layer constraints, i.e. throughput reduction compared to the theoretical throughput of a single virtual channel due to a transmission power limit for any bonding size.

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Computationally Efficient Modulation Level Classification Based on Probability Distribution Distance Functions

We present a novel modulation level classification (MLC) method based on probability distribution distance functions. The proposed method uses modified Kuiper and Kolmogorov-Smirnov distances to achieve low computational complexity and outperforms the state of the art methods based on cumulants and goodness-of-fit tests. We derive the theoretical performance of the proposed MLC method and verify it via simulations. The best classification accuracy, under AWGN with SNR mismatch and phase jitter, is achieved with the proposed MLC method using Kuiper distances.

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Practical Rate and Route Adaptation with Efficient Link Quality Estimation for IEEE 802.11b/g Multi-Hop Networks

Accurate and fast packet delivery rate (PDR) estimation, used in evaluating wireless link quality, is a prerequisite to increase the performance of mobile, multi-hop and multi-rate wireless ad hoc networks. Unfortunately, contemporary PDR estimation methods, i.e. beacon-based packet counting in Estimated Transmission Time and Expected Transmission Count metrics, have unsatisfactory performance. Therefore, in this paper we propose a novel PDR estimation method based on SNR profiles. We classify all possible link quality estimation methods and compare them analytically against our design. Results show that it leads to a more efficient link quality estimation. Further investigations with the prototype implementation of our method in IEEE 802.11b/g testbeds reveal that the accuracy of PDR estimation in mobile scenarios can be improved up to 50% in comparison to generic packet-based PDR. Experiments with the same prototype on link and routing layers for different measurement scenarios show that it leads to a better rate adaptation and route selection in the form of end-to-end throughput increase compared to traditional packet counting methods.

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