On Low-Complexity SINR Feasibility Checking and Joint Power and Admission Control in Prioritized Multi-tier Cellular Networks Under Co-Channel Deployment (original) (raw)
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arXiv (Cornell University), 2015
Next generation cellular networks will consist of multiple tiers of cells and users associated with different network tiers may have different priorities (e.g., macrocell-picocellfemtocell networks with macro tier prioritized over pico tier, which is again prioritized over femto tier). Designing efficient joint power and admission control (JPAC) algorithms for such networks under a co-channel deployment (i.e., underlay) scenario is of significant importance. Feasibility checking of a given target signal-to-noise-plus-interference ratio (SINR) vector is generally the most significant contributor to the complexity of JPAC algorithms in single/multi-tier underlay cellular networks. This is generally accomplished through iterative strategies whose complexity is either unpredictable or of O(M 3), when the wellknown relationship between the SINR vector and the power vector is used, where M is the number of users/links. In this paper, we derive a novel relationship between a given SINR vector and its corresponding uplink/downlink power vector based on which the feasibility checking can be performed with a complexity of O(B 3 + M B), where B is the number of base stations. This is significantly less compared to O(M 3) in many cellular wireless networks since the number of base stations is generally much lower than the number of users/links in such networks. The developed novel relationship between the SINR and power vector not only substantially reduces the complexity of designing JPAC algorithms, but also provides insights into developing efficient but low-complexity power update strategies for prioritized multi-tier cellular networks. We propose two such algorithms and through simulations, we show that our proposed algorithms outperform the existing ones in prioritized cellular networks.
Distributed priority-based power and admission control in cellular wireless networks
2013
A distributed priority-based power and admission control algorithm is presented to address the priority-based gradual removal problem in cellular wireless networks. We assume that there exist two classes of priority for users (highpriority users versus low-priority users) and minimal number of low-priority users should be gradually removed, subject to the constraint that all high-priority users are supported with their target signal-to-interference-plus-noise ratios (SINRs) which is assumed feasible. In our proposed algorithm, each highpriority user rigidly tracks its target-SINR by employing the conventional target-SINR tracking power control algorithm, and each transmitting low-priority user tracks its target-SINR as long as its required transmit power is below a threshold, otherwise it temporarily removes itself. Each removed low-priority user resumes its transmission if the required transmit power to reach its target-SINR goes below a given threshold which is different from the former. Of these two thresholds, whose values are analytically obtained, the former is provided by the base station and the latter is obtained in a distributed manner as a function of the former. We show that the distributed power-update function corresponding to our proposed algorithm has at least one fixedpoint which is not unique in general. The convergence point, where our proposed algorithm potentially converges to, depends on initial transmit power levels of users. We also show that our proposed algorithm, at each of its fixed-points, not only provides all high-priority users with their (feasible) target-SINRs but also guarantees that no low-priority user is erroneously removed (i.e., no additional low priority user can be supported along with currently supported users). Furthermore, for the special case of tracking a common target-SINR by all low-priority users, we show that our proposed algorithm minimizes the outage-ratio of low-priority users subject to zero-outage-ratio of high-priority users. Simulation results confirm our analytical developments and show that our proposed priority-based power and admission control algorithm solves the priority-based gradual removal problem efficiently.
Threshold priority policy for channel assignment in cellular networks
IEEE Transactions on Computers, 1997
This paper presents a new policy called the threshold priority policy (TPP) for assigning channels in cellular networks. The performance of TPP is compared with the performance of the wellknown cutoff priority policy (CPP) and the nonprioritized complete sharing policy (CSP). Several numerical experiments are done for various values of offered load and portable mobility. The results are compared using three unified performance metrics which take into account the trade-off between new call blocking probability and the forced termination probability.
IEEE Transactions on Vehicular Technology, 2018
We study the inter-cell interference coordination (ICIC) problem in a multicell orthogonal frequency division multiple access based cellular network employing universal frequency reuse. In each cell, only a subset of the available subchannels are allocated to mobile stations (MSs) in a given time slot so as to limit the interference to neighboring cells; also, each base station (BS) uses a fixed transmit power on every allocated subchannel. The objective is to allocate the available subchannels in each cell to the MSs in the cell for downlink transmissions taking into account the channel qualities from BSs to MSs as well as traffic requirements of the MSs so as to maximize the weighted sum of throughputs of all the MSs. First, we show that this problem is NPcomplete. Next, we show that when the potential interference levels to each MS on every subchannel are above a threshold (which is a function of the transmit power and the channel gain to the MS from the BS it is associated with), the problem can be optimally solved in polynomial-time via a reduction to the matching problem in bipartite graphs. We also formulate the ICIC problem as a noncooperative game, with each BS being a player, and prove that although it is an ordinal potential game in two special cases, it is not an ordinal potential game in general. Also, we design two heuristic algorithms for the general ICIC problem: a greedy distributed algorithm and a simulated annealing (SA) based algorithm. The distributed algorithm is fast and requires only message exchanges among neighboring BSs. The SA algorithm is centralized and allows a tradeoff between quality of solution and execution time via an appropriate choice of parameters. Our extensive simulations show that the total throughput obtained using the better response (BR) algorithm, which is often used in game theory, is very small compared to those obtained using the SA and greedy algorithms; however, the execution time of the BR algorithm is much smaller than those of the latter two algorithms. Finally, the greedy algorithm outperforms the SA algorithm in dense cellular networks and requires only a small fraction of the number of computations required by the latter algorithm for execution.
Matching theory for priority-based cell association in the downlink of wireless small cell networks
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.
2013 IEEE Global Communications Conference (GLOBECOM), 2013
In heterogeneous cellular networks, the deployment of low-powered picocells provides user offloading and capacity enhancement. The expansion of a picocell's coverage by adding a positive bias for cell association can maximize these effects. Under this circumstance, downlink cross-tier interference from a macro base station to pico mobile stations in the expanded picocell range deteriorates those pico mobile stations' performance significantly. In this paper, a coordinated scheduling and power control algorithm is proposed, whereby the macro base station reduces its transmission power for those victim pico mobile stations in the expanded picocell range only on a set of resource blocks to minimize performance degradation at the macro base station. First, the transmission power level is calculated based on the mobile stations' channel condition and QoS requirements. Then, a set of resource blocks is determined by solving a binary integer programming to minimize the sum of transmission power reduction subject to victim pico mobile stations' QoS constraints. To reduce computational complexity, we utilize a heuristic algorithm, i.e., max-min greedy method, to solve the problem. Through system level simulations, we show that average and 5%-ile throughputs of victim pico mobile stations are significantly improved.
Fast Algorithms for Resource Allocation in Cellular Networks
We consider a scheduled orthogonal frequency division multiplexed (OFDM) wireless cellular network where the channels from the base-station to the mobile users undergo flat fading. Spectral resources are to be divided among the users in order to maximize total user utility. We show that this problem can be cast as a nonlinear convex optimization problem, and describe an ( ) algorithm to solve it. Computational experiments show that the algorithm typically converges in around 25 iterations, where each iteration has a cost that is ( ), with a modest constant. When the algorithm starts from an initial resource allocation that is close to optimal, convergence typically takes even fewer iterations. Thus, the algorithm can efficiently track the optimal resource allocation as the channel conditions change due to fading. We also show how our techniques can be extended to solve resource allocation problems that arise in wideband networks with frequency selective fading and when the utility of a user is also a function of the resource allocations in the past.
A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks
Journal of Network and Computer Applications, 2012
The major driver for deploying next generation wireless cellular systems is their ability to efficiently deliver resource-demanding services, many of which require symmetric communication between an uplink mobile user and a downlink mobile user that belong to the same network. In this work, we propose a utility-based joint uplink/downlink scheduling algorithm suitable for wireless services involving pairwise communication among mobile users. While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. By jointly considering the time varying channel conditions in both the uplink and the downlink directions, the proposed algorithm avoids wasting of resources and achieves notable performance gains in terms of increased number of active connections, lower packet drop rate, and increased network throughput. These gains are achieved with a tradeoff cost in terms of complexity and signaling overhead. For overhead reduction in practical scenarios, we propose an implementation over clusters within the network.
Uplink Blocking Probabilities in Priority-Based Cellular CDMA Networks with Finite Source Population
IEICE Transactions on Communications, 2016
Fast proliferation of mobile Internet and high-demand mobile applications necessitates the introduction of different priority classes in next-generation cellular networks. This is especially crucial for efficient use of radio resources in the heterogeneous and virtualized network environments. Despite the fact that many analytical tools have been proposed for capacity and radio resource modelling in cellular networks, only a few of them explicitly incorporate priorities among services. We propose a novel analytical model to analyse the performance of a prioritybased cellular CDMA system with finite source population. When the cell load is above a certain level, low-priority calls may be blocked to preserve the quality of service of high-priority calls. The proposed model leads to an efficient closed-form solution that enables fast and very accurate calculation of resource occupancy of the CDMA system and call blocking probabilities, for different services and many priority classes. To achieve them, the system is modelled as a continuous-time Markov chain. We evaluate the accuracy of the proposed analytical model by means of computer simulations and find that the introduced approximation errors are negligible.
Femtocell Association in Two-Tier Cellular Networks: Complexity and Efficient Algorithms
This research considers the problem of base station association in a small cell environment. The wireless network in consideration is of two-tiers, where randomly dispersed overlay femtocell base stations (FBSs) coexist with a macrocell base station (MBS). The paper considers two optimization problems, maximizing the set of associated users and maximizing the set of weighted associated users by the FBSs, subject to signal-to-interference-plus-noise ratio (SINR) requirements as well as the quality of service (QoS) of the macrocell user. Both problems are formulated as linear integer programs. The second problem is known to be NP-hard. We prove that the first problem is NP-hard too. Because of the NP-hardness, efficient heuristic algorithms are required in practice. This work develops two heuristic polynomial time algorithms to solve both problems. The computational complexity of the proposed algorithms and the brute force (BF) algorithm are evaluated. Moreover the paper benchmarks the performance of the proposed algorithms in comparison to optimal and industry standard algorithms, through numerical simulations. The results demonstrate the efficiency of the proposed algorithms in terms of complexity and sub-optimality. They also show that the weighted problem can be solved to provide solutions that are fair between the users and load balance among femtocells.