General Network Scenario Research Articles

Interference Prediction in Wireless Networks: Stochastic Geometry Meets Recursive Filtering

This article proposes and evaluates a technique to predict the level of interference in wireless networks. We design a recursive predictor that estimates future interference values by filtering measured interference at a given location. The predictor's parameterization is done offline by translating the autocorrelation of interference into an autoregressive moving average (ARMA) representation. This ARMA model is inserted into a steady-state Kalman filter enabling nodes to predict with low computational effort. Results show a good accuracy of predicted values versus true values for relevant time horizons. Although the predictor is parameterized for Poisson-distributed nodes, Rayleigh fading, and fixed message lengths, a sensitivity analysis shows that it also tends to work well in more general network scenarios. Numerical examples for underlay device-to-device communications, a common wireless sensor technology, and coexistence scenarios of Wi-Fi and LTE illustrate its broad applicability. The predictor can be applied as part of interference management to improve medium access, scheduling, and radio resource allocation.

Modeling and parameter analysis of IEEE 802.15.4-based networks and the metering application

As the support of wireless sensor networks expands to various application scenarios, the communication environments and the performance requirements of different application scenarios vary a lot. To cope with different communication environments and performance requirements, both data transmission ability and medium access ability are equivalently important. In this article, a joint analytical model is proposed to fully and precisely estimate networks’ communication performance, energy efficiency, and scalability. In the proposed model, both the physical layer’s and medium access control layer’s key parameters are taken into consideration. By comparing with OPNET-based simulation model, the rationality of the proposed analytical model is first validated under a wide range of network scenarios. Then, a series of simulations under general network scenarios and metering network scenarios are conducted. With these simulations, the performance of adjusting both layers’ parameters in improving communication performance and energy efficiency was proved superior to single-layer’s parameter optimizations. Finally, by comparing the available range of different key parameters’ optimal value under different network scenarios, the maximum backoff numbers and the minimum backoff exponent are considered to be the most effective parameters for metering network optimization.

A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs

This paper considers proportional fairness amongst ACs in an EDCA WLAN for provision of distinct QoS requirements and priority parameters. A detailed theoretical analysis is provided to derive the optimal station attempt probability which leads to a proportional fair allocation of station throughputs. The desirable fairness can be achieved using a centralised adaptive control approach. This approach is based on multivariable state-space control theory and uses the Linear Quadratic Integral (LQI) controller to periodically update CWmin till the optimal fair point of operation. Performance evaluation demonstrates that the control approach has high accuracy performance and fast convergence speed for general network scenarios. To our knowledge this might be the first time that a closed-loop control system is designed for EDCA WLANs to achieve proportional fairness.

Distributed Sensing and Transmission of Sporadic Random Samples Over a Multiple-Access Channel

This work considers distributed sensing and transmission of sporadic random samples. Lower bounds are derived for the reconstruction error of a single normally or uniformly-distributed finite-dimensional vector imperfectly measured by a network of sensors and transmitted with finite energy to a common receiver via an additive white Gaussian noise asynchronous multiple-access channel. Transmission makes use of a perfect causal feedback link to the encoder connected to each sensor. A retransmission protocol inspired by the classical scheme in [1] applied to the transmission of single and bi-variate analog samples analyzed in [2] and [3] is extended to the more general network scenario, for which asymptotic upper-bounds on the reconstruction error are provided. Both the upper and lower-bounds show that collaboration can be achieved through energy accumulation under certain circumstances. In order to investigate the practical performance of the proposed retransmission protocol we provide a numerical evaluation of the upper-bounds in the non-asymptotic energy regime using low-order quantization in the sensors. The latter includes a minor modification of the protocol to improve reconstruction fidelity. Numerical results show that an increase in the size of the network brings benefit in terms of performance, but that the gain in terms of energy efficiency diminishes quickly at finite energies due to a non-coherent combining loss.

Bargaining‐based spectrum sharing in cognitive radio network

SUMMARYCognitive radio (CR) can significantly alleviate the network pressure caused by the rapid development of wireless communications through allowing secondary users (SUs) to obtain spectrum resource from primary users (PUs). One key issue of CR technology is spectrum sharing, that is, how spectrum should be allocated between SUs without causing interference to PUs. In this paper, we propose a bilateral bargaining mechanism to achieve this goal between two SUs. The general network scenario with multiple SUs can be decomposed into multiple pairs of bilateral bargaining studied in this paper. The SUs have to reach a mutual satisfactory agreement on the partition of spectrum by making alternating offers to each other. We model such bargaining process as dynamic finite/infinite horizon multistage game with observed actions and fully characterize the corresponding subgame perfect equilibria. Moreover, theoretical analysis and numerical results indicate that our proposed scheme can effectively allocate spectrum resource between SUs. Copyright © 2012 John Wiley & Sons, Ltd.

Efficient Wireless Extension Point Placement Algorithm in Urban Rectilineal WLANs

With a small amount of software modification, wireless extension points (EPs), which are now commercially available, can be used to improve the throughput capacity of a wireless local area network (WLAN). An EP is an immobile device that has access to the power supply or is equipped with a high-capacity battery but does not have direct access to the Internet. They wirelessly relay data between the access point and the mobile hosts. In this paper, we investigate the optimal placement of the EPs such that the throughput capacity of an urban rectilineal WLAN can be maximized. Two channel models that are based on the Shannon capacity bound and IEEE 802.11 specifications are studied. We first formulate a solution for the optimal EP placement problem in a general network scenario as a nonlinear programming problem; then, we propose an efficient algorithm that determines the optimal locations of a fixed number of EPs in a rectilineal network. Our results show that, for a wide range of system parameters, the optimally placed EPs can significantly increase the network throughput capacity. Moreover, we study how the number of EPs, transmission power, path loss exponent, channel models, and traffic characteristics affect the optimal EP placement and expected throughput capacity of the network.

On the Capacity of Wireless Sensor Networks with Omnidirectional Antennas

We establish some new results on the capacity of wireless sensor networks that employ single-user - detection, and we present the implications of our r esults on the scalability of such networks. In particular, we find bounds on the maximum achievable per-sensor end-to-end throughput, λe, and the maximum number of simultaneously successful wireless transmissions, Nt max , under a more general network scenario than previously considered . Furthermore, in the derivation of our results, we m ake no restrictions on the mobility pattern of the sensor and the destination nodes or on the number simultaneous transmissions and/or receptions that the nodes are capable of maintaining. In our derivation, we also analyze the effect of parameters such as the area of the network domai n, A, the path loss exponent, γ, the processing gain, G, and the SINR threshold, β. Specifically, we prove the following results for a wireless sensor network of N sensor nodes and M destination nodes that are equipped with omnidirec tional antennas:

On the scalability and capacity of planar wireless networks with omnidirectional antennas

An Erratum has been published for this article in Wireless Communications and Mobile Computing 2004; 4(4): 473. We extend the previously well-known results on the capacity of wireless networks and present the implications of our results on network scalability. In particular, we find bounds on the maximum achievable per-node end-to-end throughput, λe, and the maximum number of simultaneously successful wireless transmissions, Ntmax, under a more general network scenario than previously considered. Furthermore, in the derivation of our results, we make no restrictions on the mobility pattern of the nodes or on the number simultaneous transmissions and/or receptions that nodes are capable of maintaining. In our derivation, we analyze the effect of parameters such as the area of the network domain, A, the path loss exponent, γ, the processing gain, G, and the SINR threshold, β. Specifically, we prove the following results for a wireless network of N nodes that are equipped with omnidirectional antennas: (1) λe is Θ(1/N) under very general conditions. This result continues to hold even when the communication bandwidth is divided into sub-channels of smaller bandwidth. (2) Ntmax has an upper bound that does not depend on N, which is the simultaneous transmission capacity of the network domain, NtQ. For a circular network domain, NtQ is O(Amin{γ/2,1}) if γ≠2 and O(A/log(A)) if γ = 2. In addition, NtQ is O(γ2) and O(G/β). Moreover, lack of attenuation and lack of space are equivalent, where NtQ cannot exceed 1 + G/β. (3) As N ∞ a desired per-node end-to-end throughput is not achievable, unless the average number of hops between a source and a destination does not grow indefinitely with N, A grows with N and N is O(Amin{γ/2,1}) if γ≠2 and O(A/log(A)) if γ = 2. Copyright © 2004 John Wiley & Sons, Ltd.