Ioannis G. Fraimis

User selection and resource allocation algorithm with fairness in MISO-OFDMA

Evaluating wireless mesh network performances has become a specific challenge since the emergence of ubiquitous computing. In this article, we consider the network capacity as the performance measure and study its behaviour under two different interference models: (i) usual IEEE 802.11 MAC layer with acknowledgments at each hop, and (ii) block acknowledgments reported at the transport layer that can be included in the IEEE 802.16 standard. We derive a linear program modeling crosslayer characteristics of the wireless mesh network that is solved using column generation. We quantify the capacity gain induced by the move of the MAC acknowledgments into the transport layer, and show that a better load distribution is also obtained.Evaluating wireless mesh network performances has become a specific challenge since the emergence of ubiquitous computing. In this article, we consider the network capacity as the performance measure and study its behaviour under two different interference models: (i) usual IEEE 802.11 MAC layer with acknowledgments at each hop, and (ii) block acknowledgments reported at the transport layer that can be included in the IEEE 802.16 standard. We derive a linear program modeling crosslayer characteristics of the wireless mesh network that is solved using column generation. We quantify the capacity gain induced by the move of the MAC acknowledgments into the transport layer, and show that a better load distribution is also obtained.

A Decentralized Subchannel Allocation Scheme with Inter-Cell Interference Coordination (ICIC) for Multi-Cell OFDMA Systems

Inter-cell interference (ICI) is responsible for user throughput degradation and especially for users found near cell border which additionally experience serious path-losses. Efficient methods for ICI mitigation are ICI coordination (ICIC) schemes which allocate certain resources among users in different cells. In this paper we propose a decentralized ICIC scheme in order to mitigate the ICI and enhance the capacity of the users found near the cell-edge area of a wireless multi-cell OFDMA system. Key features of the proposed scheme are the subchannel the allocation in a user selective manner considering instantaneous channel conditions and subchannel reuse minimization. The multi-cell subchannel allocation problem is decomposed into a distributed single-cell optimization problem with inter-cell coordination facilitaded by interfaces similar to X2 in 3GPP Long Term Evolution (LTE) networks. We prove through simulation that the proposed scheme yields better performance than existing conventional schemes.

QoS-Based Proportional Fair Allocation Algorithm for OFDMA Wireless Cellular Systems

In this paper, a resource allocation algorithm which provides Quality of Service (QoS) guarantees to users, in a cellular Orthogonal Frequency Division Multiple Access (OFDMA) network is proposed. The algorithm is a modified proportional fair (PF) scheduling algorithm and it comprises two phases. In the first phase, users minimum data rate requirements are met and in the second phase, remaining resources are allocated according to PF scheduling algorithm. It is a cell-level algorithm and its main advantages are the low implementation complexity and the capacity of maintaining higher ratio of QoS satisfied users than other reference schemes. Via simulation we show that our scheme outperforms other reference resource allocation schemes.

A distributed radio resource allocation algorithm with interference coordination for multi-cell OFDMA systems

Inter-cell interference is a major problem in multi-cell OFDMA systems and can severely degrade the system throughput, particularly for cell-edge users. An efficient technique to mitigate inter-cell interference (ICI), is interference coordination that allocates certain resources among users in different cells. In this paper, we propose a novel and distributed algorithm in order to mitigate the inter-cell interference and enhance the capacity of the users near the cell-edge area of a multi-cellular network configuration. The main characteristics of the algorithm are the bandwidth allocation in a user selective manner and the collision avoidance with subchannels in use by users in neighboring cells. The algorithm requires coordination between base stations (BSs) in the sense that the cell-edge bands in adjacent cells should be orthogonal and channel occupancy state of each cell must be known to its neighboring cells. It is shown that the proposed algorithm has better performance than existing conventional schemes. Thus, our algorithm can be applied in next generation cellular systems 3GPP Long Term Evolution (LTE) and IEEE 802.16m.

Fairness-Aware Resource Allocation for the SISO Downlink over Frequency-Selective Channels

The problem of resource allocation for the downlink of wireless systems operating over a frequency-selective channel is investigated. It is assumed that both the Base Station (BS) and each user are equipped with a single antenna (Single Input Single Output - SISO case) and Orthogonal Frequency Division Multiple Access (OFDMA) is used as a multiple access scheme. A suboptimal, but efficient scheme is devised in order to maximize the sum of the users data rates subject to constraints on total available power and proportional fairness among users data rates. It is shown, via simulation, that the proposed resource allocation scheme not only achieves higher sum of the users data rates than other existing schemes but also sum data rate is distributed fairly and flexibly among users. Thus, the scheme can be applied to latest-generation wireless systems that provide Quality-of-Service guarantees.

A Novel Fairness-Aware Resource Allocation Scheme in Multiuser SISO-OFDMA Downlink

The problem of resource allocation for the downlink of wireless systems operating over a frequency-selective channel is investigated. It is assumed that both the Base Station (BS) and each user are equipped with a single antenna (Single Input Single Output-SISO case), and Orthogonal Frequency Division Multiple Access (OFDMA) is used as a multiple access scheme. The aim is to maximize the sum of the users data rates subject to constraints on total available power and proportional fairness among users data rates. Achieving the optimal solution has a high computational cost thereby the use of suboptimal techniques is necessary. A suboptimal, but efficient, scheme is devised, and it is shown, via simulation, that not only the proposed resource allocation scheme achieve higher sum of the users data rates than other existing schemes but also the sum data rate is distributed fairly and flexibly among users. In addition, the proposed scheme is complexity effective and can be applied to latest-generation wireless systems that provide Quality-of-Service (QoS) guarantees.

Queue-Aware Resource Allocation for Multi-cell OFDMA Systems with QoS Provisioning

This paper proposes a queue-aware resource allocation algorithm which provides quality of service (QoS) guarantees. The proposed solution adopts a cross-layer design approach since it is aware of both users’ queue buffer states (data link layer) and channel quality state (physical layer). Main advantages of the proposed resource allocation algorithm are: the low computational complexity and its capacity of maintaining lower QoS violation probability than other multi-cellular schemes. The proposed solution can also result in enhanced cell-edge data rate and improved fairness performance. User minimum data rate and target bit error rate as considered as QoS parameters. Validation of the proposed algorithm is achieved through various simulation scenarios wherein QoS violation probability, system fairness, user average data rate and cell-edge throughput are investigated. Numerical results and complexity analysis demonstrate the efficiency and the feasibility of the proposed QoS-oriented approach.

Fairness‐aware user selection and resource allocation in MISO‐OFDMA

The problem of user selection and resource allocation for the downlink of wireless systems operating over a frequency-selective channel is investigated. It is assumed that the Base Station (BS) uses many antennas, whereas a single antenna is available to each user (Multiple Input Single Output—MISO case). To relieve heavy computational burden, a suboptimal, but efficient algorithm is devised that is based on Zero Forcing (ZF) beamforming and is less complex than other approaches. The algorithm maximises the sum of the users data rates subject to constraints on total available power and proportional fairness among users data rates. Simulation results are provided to indicate that the algorithm can satisfy the fairness criterion. Thus, the algorithm can be applied to latest-generation wireless systems that provide Quality-of-Service (QoS) guarantees. Copyright

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.

Resource allocation algorithm for MIMO-OFDMA systems with minimum resources guarantee

The problem of resource allocation for the downlink of wireless systems operating over a frequency-selective channel is investigated. It is assumed that the BS (Base Station) uses many antennas and many antennas are available for each user too (Multiple Input Multiple Output - MIMO case). To relieve heavy computational burden, a suboptimal, but efficient algorithm is devised that maximizes the sum of the users data rates subject to total available power constraint while guaranteeing minimum resources for each user. Simulation results are provided to prove our statements. Thus, the algorithm can be applied to latest-generation wireless systems that provide Quality-of-Service (QoS) guarantees.