Fair Radio Resource Allocation Research Articles

Adaptive priority-based fair-resource allocation for MIMO-OFDM multicast networks

In MIMO-OFDM multicast networks, sub-carrier allocation for real-time and non-real time users is complex due to delay and throughput issues. In order to overcome these issues, in this paper, we propose to develop a priority-based fair-radio resource allocation for MIMO-OFDMA-based multicast system. Initially, the multicast groups are classified as RT, NRT and BE. Then priorities are assigned for the groups based on the QoS requirements such as delay tolerance, packet dropping rate and transmission rate. When the priority value of a group is greater than the priority threshold, then the resource is allocated to the relevant group as per fair resource allocation technique. Overall this technique improves the sub-carrier allocation for real-time and non-real time users in terms of spectral efficiency and fairness. By simulation results, we show that the proposed technique enhances the average throughput, spectral efficiency, sub-carrier distribution for each class of users.

Adaptive priority-based fair-resource allocation for MIMO-OFDM multicast networks

In MIMO-OFDM multicast networks, sub-carrier allocation for real-time and non-real time users is complex due to delay and throughput issues. In order to overcome these issues, in this paper, we propose to develop a priority-based fair-radio resource allocation for MIMO-OFDMA-based multicast system. Initially, the multicast groups are classified as RT, NRT and BE. Then priorities are assigned for the groups based on the QoS requirements such as delay tolerance, packet dropping rate and transmission rate. When the priority value of a group is greater than the priority threshold, then the resource is allocated to the relevant group as per fair resource allocation technique. Overall this technique improves the sub-carrier allocation for real-time and non-real time users in terms of spectral efficiency and fairness. By simulation results, we show that the proposed technique enhances the average throughput, spectral efficiency, sub-carrier distribution for each class of users.

Fair Radio Resource Allocation for MIMO OFDM-based Multicast Systems

This paper investigates the problem of resource allocation in a multiple-input multiple-output (MIMO) OFDM-based system, wherein multiple multicast groups exist. Multicasting is a transmission technique which enables a transmitter to communicate via a single wireless link with multiple receivers simultaneously. Moreover, the presence of multiple antennas in both transmitter and receiver enhances significantly the system spectral efficiency. MIMO technology along with multicasting offers major advantages to wireless systems. However, optimum exploitation of these technologies adds significant complexity to the system which makes very difficult any possible practical implementation. Another important issue of such systems is their capacity to ensure to all users a certain level of QoS. To that end, we propose a low complexity fair resource allocation algorithm aiming at ensuring a certain amount of resources to all users when multicasting is applied. Validation of the proposed solution is achieved through extensive simulation and it is compared to other multicast schemes for MIMO systems which exist in literature. Numerical results and complexity analysis show the feasibility of the proposed algorithm.

A Fair Radio Resource Allocation Algorithm for Uplink of FBMC Based CR Systems

Spectrum scarcity seems to be the most challenging issue to be solved in new wireless telecommunication services. It is shown that spectrum unavailability is mainly due to spectrum inefficient utilization and inappropriate physical layer execution rather than spectrum shortage. Daily increasing demand for new wireless services with higher data rate and QoS level makes the upgrade of the physical layer modulation techniques inevitable. Orthogonal Frequency Division Multiple Access (OFDMA) which utilizes multicarrier modulation to provide higher data rates with the capability of flexible resource allocation, although has widely been used in current wireless systems and standards, seems not to be the best candidate for cognitive radio systems. Filter Bank based Multi-Carrier (FBMC) is an evolutionary scheme with some advantages over the widely-used OFDM multicarrier technique. In this paper, we focus on the total throughput improvement of a cognitive radio network using FBMC modulation. Along with this modulation scheme, we propose a novel uplink radio resource allocation algorithm in which fairness issue is also considered. Moreover, the average throughput of the proposed FBMC based cognitive radio is compared to a conventional OFDM system in order to illustrate the efficiency of using FBMC in future cognitive radio systems. Simulation results show that in comparison with the state of the art two algorithms (namely, Shaat and Wang) our proposed algorithm achieves higher throughputs and a better fairness for cognitive radio applications.

Terminal-Modality-Based Joint Call Admission Control Algorithm for Fair Radio Resource Allocation in Heterogeneous Cellular Networks

There is a problem of unfairness in allocation of radio resources among heterogeneous mobile terminals in heterogeneous wireless networks. Low-capability mobile terminals (such as single-mode terminals) suffer high call blocking probability whereas high-capability mobile terminals (such as quad-mode terminals) experience very low call blocking probability, in the same heterogeneous wireless network. This paper proposes a Terminal-Modality-Based Joint Call Admission Control (TJCAC) algorithm to reduce this problem of unfairness. The proposed TJCAC algorithm makes call admission decisions based on mobile terminal modality (capability), network load, and radio access technology (RAT) terminal support index. The objectives of the proposed TJCAC algorithm are to reduce call blocking/dropping probability, and ensure fairness in allocation of radio resources among heterogeneous mobile terminals in heterogeneous networks. An analytical model is developed to evaluate the performance of the proposed TJCAC scheme in terms of call blocking/dropping probability in a heterogeneous wireless network. The performance of the proposed TJCAC algorithm is compared with that of other JCAC algorithms. Results show that the proposed algorithm reduces call blocking/dropping probability in the networks, and ensure fairness in allocation of radio resources among heterogeneous terminals.

Multi-domain WLAN load balancing in WLAN/WPAN interference environments

The proliferation of wireless local area network (WLAN) deployments in enterprises, public areas, and homes will likely cause frequent geographical coverage overlap among multiple networks. A recent growing interest is the coordination among WLAN providers for efficient network management over a large coverage area. While radio resource management for a single WLAN has been studied extensively, little research work addresses resource management over multiple domains. When multiple WLANs co-locate in a small geographic vicinity, the lack of cooperative multi-domain resource management can cause significant performance degradation due to inter-domain interference. Unbalanced loads among multiple networks can incur congestion in a few WLANs while foregoing unused excess resources in others. Moreover, since WLANs often operate in unlicensed frequency bands shared by various public and private networks, they must cope with the dynamic RF environment involving a diverse set of interference sources. This paper introduces a new cooperative load balancing framework for multi-domain WLANs operating in an interference environment. A third-party-based architecture is proposed to facilitate fair radio resource allocation among multiple networks. The proposed third-party agent collects observed network state information from different WLANs and optimizes resource usage. Under the proposed scheme, resource utilization and co-channel interference can be adaptively balanced across the entire integrated system. The impact of other co-located interference sources in the operational environment are taken into account in the optimization process. The proposed load balancing framework for interference environments is a complement to the interference mitigation mechanisms operated at the PHY/MAC layer. Simulation results show that the proposed multi-domain load balancing scheme outperforms other schemes which do not consider interdomain interference or environmental interference.