Low-complexity medium access control protocols for QoS support in third-generation radio access networks

One approach to maximizing the efficiency of medium access control (MAC) on the uplink in a future wideband code-division multiple-access (WCDMA)-based third-generation radio access network, and hence maximize spectral efficiency, is to employ a low-complexity distributed scheduling control approach. The maximization of spectral efficiency in third-generation radio access networks is complicated by the need to provide bandwidth-on-demand to diverse services characterized by diverse quality of service (QoS) requirements in an interference limited environment. However, the ability to exploit the full potential of resource allocation algorithms in third-generation radio access networks has been limited by the absence of a metric that captures the two-dimensional radio resource requirement, in terms of power and bandwidth, in the third-generation radio access network environment, where different users may have different signal-to-interference ratio requirements. This paper presents a novel resource metric as a solution to this fundamental problem. Also, a novel deadline-driven backoff procedure has been presented as the backoff scheme of the proposed distributed scheduling MAC protocols to enable the efficient support of services with QoS imposed delay constraints without the need for centralized scheduling. The main conclusion is that low-complexity distributed scheduling control strategies using overload avoidance/overload detection can be designed using the proposed resource metric to give near optimal performance and thus maintain a high spectral efficiency in third-generation radio access networks and that importantly overload detection is superior to overload avoidance

A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing

Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness

This paper addresses coordinated downlink beamforming optimization in multicell time-division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on the Pareto boundary with max-min rate fairness, we first develop a two-step centralized optimization algorithm to design the joint beamforming vectors. This algorithm can achieve a further sum-rate improvement over the max-min optimal performance, and is shown to guarantee max-min Pareto optimality for scenarios with two base stations (BSs) each serving a single user. To realize a distributed solution with limited intercell communication, we then propose an iterative algorithm by exploiting an approximate uplink-downlink duality, in which only a small number of positive scalars are shared between cells in each iteration. Simulation results show that the proposed distributed solution achieves a fairness rate performance close to the centralized algorithm while it has a better sum-rate performance, and demonstrates a better tradeoff between sum-rate and fairness than the Nash Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201

A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

This paper presents a novel framework for modeling the uplink intercell interference (ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.Comment: IEEE Transactions on Wireless Communications, 2013. arXiv admin note: substantial text overlap with arXiv:1206.229

Dynamic Almost Blank Subframe Scheme for Enhanced Intercell Interference Coordination in LTE-A Heterogeneous Networks

In LTE-A heterogeneous network, traffic load may be distributed unequally because the transmission power of macro eNodeB (eNB) is higher than pico eNB. To address the coverage problems resulting from nodes with different transmission powers, cell range expansion (CRE) technique has been proposed as a cell selection technique. However, in this case, the intercell interference (ICI) problem can occur on both data and control channels when users connect to pico eNB. To mitigate ICI problem, a new dynamic almost blank subframe (ABS) scheme is proposed in this paper. In this scheme, a fuzzy logic system is deployed to monitor the system performance and then obtain the required number of ABSs. Simulation results show that the cell throughput and user throughput can be improved using the proposed dynamic ABS scheme

Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition

This paper studies joint beamforming and power control in a coordinated multicell downlink system that serves multiple users per cell to maximize the minimum weighted signal-to-interference-plus-noise ratio. The optimal solution and distributed algorithm with geometrically fast convergence rate are derived by employing the nonlinear Perron-Frobenius theory and the multicell network duality. The iterative algorithm, though operating in a distributed manner, still requires instantaneous power update within the coordinated cluster through the backhaul. The backhaul information exchange and message passing may become prohibitive with increasing number of transmit antennas and increasing number of users. In order to derive asymptotically optimal solution, random matrix theory is leveraged to design a distributed algorithm that only requires statistical information. The advantage of our approach is that there is no instantaneous power update through backhaul. Moreover, by using nonlinear Perron-Frobenius theory and random matrix theory, an effective primal network and an effective dual network are proposed to characterize and interpret the asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on Wireless Communications are correcte

Interference Management Based on RT/nRT Traffic Classification for FFR-Aided Small Cell/Macrocell Heterogeneous Networks

Cellular networks are constantly lagging in terms of the bandwidth needed to support the growing high data rate demands. The system needs to efficiently allocate its frequency spectrum such that the spectrum utilization can be maximized while ensuring the quality of service (QoS) level. Owing to the coexistence of different types of traffic (e.g., real-time (RT) and non-real-time (nRT)) and different types of networks (e.g., small cell and macrocell), ensuring the QoS level for different types of users becomes a challenging issue in wireless networks. Fractional frequency reuse (FFR) is an effective approach for increasing spectrum utilization and reducing interference effects in orthogonal frequency division multiple access networks. In this paper, we propose a new FFR scheme in which bandwidth allocation is based on RT/nRT traffic classification. We consider the coexistence of small cells and macrocells. After applying FFR technique in macrocells, the remaining frequency bands are efficiently allocated among the small cells overlaid by a macrocell. In our proposed scheme, total frequency-band allocations for different macrocells are decided on the basis of the traffic intensity. The transmitted power levels for different frequency bands are controlled based on the level of interference from a nearby frequency band. Frequency bands with a lower level of interference are assigned to the RT traffic to ensure a higher QoS level for the RT traffic. RT traffic calls in macrocell networks are also given a higher priority compared with nRT traffic calls to ensure the low call-blocking rate. Performance analyses show significant improvement under the proposed scheme compared with conventional FFR schemes