Channel Assignment In Wireless Networks Research Articles

Minimum ply covering of points with disks and squares

Following the seminal work of Erlebach and van Leeuwen in SODA 2008, we introduce the minimum ply covering problem. Given a set P of points and a set S of geometric objects, both in the plane, our goal is to find a subset S′ of S that covers all points of P while minimizing the maximum number of objects covering any point in the plane (not only points of P). For objects that are unit squares and unit disks, this problem is NP-hard and cannot be approximated by a ratio smaller than 2. We present 2-approximation algorithms for this problem with respect to unit squares and unit disks, thus matching the lower bound. Our algorithms run in polynomial time when the optimum objective value is bounded by a constant.Motivated by channel-assignment in wireless networks, we consider a variant of the problem where the selected unit disks must be 3-colorable, i.e., colored by three colors such that all disks of the same color are pairwise disjoint. We present a polynomial-time algorithm that achieves a 2-approximate solution, i.e., a solution that is 6-colorable.We also study the weighted version of the problem in dimension one, where P consists of points and S consists of weighted intervals on a line. We present an algorithm that solves this problem in O(|P|+|S|+M)-time where M is the number of pairs of overlapping intervals. This repairs a solution claimed by Nandy, Pandit, and Roy in CCCG 2017.

Pinball attacks against Dynamic Channel assignment in wireless networks

In this paper, we expose a class of stealthy attacks, which we coin pinball attacks, that exploit the adaptive nature of Dynamic Channel Assignment algorithms in wireless networks. In a pinball attack, the attacker strategically induces interference in the neighborhood of certain nodes to cause a cascading channel switching behavior, thereby exploiting the topology of the network to his own advantage. The attacker’s problem is formulated as a Markov Decision Process in which the attacker seeks to maximize his long-term net rewards. To overcome the exponential size of the state space, we derive suboptimal attack policies through approximation methods. We expose the pinball attacks on two general setups that arise practically in wireless communication systems. In the first setup, each wireless node is an access point aiming to select a channel that has minimum interference with its neighbors. In the second setup, we consider wireless nodes with multiple antennas whereby every node should communicate with each of its neighbors on a separate channel. We formally establish the equivalence of both setups by showing that the identified pinball attack policies on one can be directly mapped to attack policies on the other. We present numerical results to assess the impact of the obtained pinball attack policies under various topologies, and show that they outperform other known attack policies over all topologies considered. We also propose a novel approach to scale up the attack to larger size networks with special structures.

Interference-Aware Channel Segregation Based Dynamic Channel Assignment for Wireless Networks

SUMMARY Recently, we proposed an interference-aware channel segregation based dynamic channel assignment (IACS-DCA). In IACS-DCA, each base station (BS) measures the instantaneous co-channel interference (CCI) power on each available channel, computes the moving average CCI power using past CCI measurement results, and selects the channel having the lowest moving average CCI power. In this way, the CCI-minimized channel reuse pattern can be formed. In this paper, we introduce the autocorrelation function of channel reuse pattern, the fairness of channel reuse, and the minimum co-channel BS distance to quantitatively examine the channel reuse pattern formed by the IACS-DCA. It is shown that the IACSDCA can form a CCI-minimized channel reuse pattern in a distributed manner and that it improves the signal-to-interference ratio (SIR) compared to the other channel assignment schemes.

Iterative Fair Channel Assignment for Wireless Networks

We introduce an orthogonal channel assignment algorithm that increases spectrum utilization via systematic re-use of channels, leveraging carrier aggregation capability supported in the latest access technologies and maintaining fairness across networks. Unlike conventional graph coloring, the proposed algorithm iterates over available channels assigning one channel at a time starting with a network with a higher priority (e.g. based on assigned channels so far) and then re-using the same channel in as many other networks as possible. Numerical results show that the proposed algorithm not only improves spectrum utilization but also well approximates the optimal solution yet with polynomial-time complexity.

Coloring Spatial Point Processes With Applications to Peer Discovery in Large Wireless Networks

In this paper, we study distributed channel assignment in wireless networks with applications to peer discovery in ad hoc wireless networks. We model channel assignment as a coloring problem for spatial point processes in which <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> nodes are located in a unit cube uniformly at random and each node is assigned one of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> colors, where each color represents a channel. The objective is to maximize the spatial separation between nodes of the same color. In general, it is hard to derive the optimal coloring algorithm, and we therefore consider a natural online greedy coloring algorithm first proposed by Ko and Rubenstein in 2005. We prove two key results: 1) with just log <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> /log log <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> colors, the distance separation achieved by the greedy coloring algorithm asymptotically matches the optimal distance separation that can be achieved by an algorithm which is allowed to optimally place the nodes but is allowed to use only one color; and 2) when K=Ω(log n), the greedy coloring algorithm asymptotically achieves the best distance separation that can be achieved by an algorithm which is allowed to both optimally color and place nodes. The greedy coloring algorithm is also shown to dramatically outperform a simple random coloring algorithm. Moreover, the results continue to hold under node mobility.

Coloring spatial point processes with applications to peer discovery in large wireless networks

In this paper, we study distributed channel assignment in wireless networks with applications to peer discovery in ad hoc wireless networks. We model channel assignment as a coloring problem for spatial point processes in which n nodes are located in a unit cube uniformly at random and each node is assigned one of K colors, where each color represents a channel. The objective is to maximize the spatial separation between nodes of the same color. In general, it is hard to derive the optimal coloring algorithm and therefore, we consider a natural greedy coloring algorithm, first proposed in [5]. We prove two key results: (i) with just a small number of colors when K is roughly of the order of log(n) loglog(n), the distance separation achieved by the greedy coloring algorithm asymptotically matches the optimal distance separation that can be achieved by an algorithm which is allowed to select the locations of the nodes but is allowed to use only one color, and (ii) when K = Omega(log(n)), the greedy coloring algorithm asymptotically achieves the best distance separation that can be achieved by an algorithm which is allowed to both optimally color and place nodes. The greedy coloring algorithm is also shown to dramatically outperform a simple random coloring algorithm. Moreover, the results continue to hold under node mobilities.

Distributed-Memory Parallel Algorithms for Distance-2 Coloring and Related Problems in Derivative Computation

The distance-2 graph coloring problem aims at partitioning the vertex set of a graph into the fewest sets consisting of vertices pairwise at distance greater than 2 from each other. Its applications include derivative computation in numerical optimization and channel assignment in radio networks. We present efficient, distributed-memory, parallel heuristic algorithms for this NP-hard problem as well as for two related problems used in the computation of Jacobians and Hessians. Parallel speedup is achieved through graph partitioning, speculative (iterative) coloring, and a bulk synchronous parallel–like organization of parallel computation. Results from experiments conducted on a PC cluster employing up to 96 processors and using large-size real-world as well as synthetically generated test graphs show that the algorithms are scalable. In terms of quality of solution, the algorithms perform remarkably well—the numbers of colors used by the parallel algorithms are observed to be very close to the numbers used by their sequential counterparts, which in turn are quite often near optimal. Moreover, the experimental results show that the parallel distance-2 coloring algorithm compares favorably with the alternative approach of solving the distance-2 coloring problem on a graph $\mathcal{G}$ by first constructing the square graph $\mathcal{G}^2$ and then applying a parallel distance-1 coloring algorithm on $\mathcal{G}^2$. Implementations of the algorithms are made available via the Zoltan toolkit.

Joint Optimal Access Point Selection and Channel Assignment in Wireless Networks

In wireless cellular networks or in other networks with single-hop communication, the fundamental access control problem pertains to access point (AP) selection and channel allocation for each user. For users in the coverage area of one AP, this involves only channel allocation. However, users that belong in the intersection of coverage areas of more than one AP can select the appropriate AP to establish connection and implicitly affect the channel assignment procedure. We address the joint problem of AP selection and channel assignment with the objective to satisfy a given user load vector with the minimum number of channels. Our major finding is that the joint problem reduces to plain channel allocation in a cellular network that emerges from the original one after executing an iterative and provably convergent clique load balancing algorithm. For linear cellular networks, our approach leads to minimum number of required channels to serve a given load vector. For 2D cellular networks, the same approach leads to a heuristic algorithm with a suboptimal solution due to the fact that clique loads cannot be balanced. Numerical results demonstrate the performance benefits of our approach in terms of blocking probability in a dynamic scenario with time-varying number of connection requests. The presented approach constitutes the basis for addressing more composite resource allocation problems in different context.

Formula omitted] labeling of d-dimensional grids

In this paper, we address the problem of λ labelings, that was introduced in the context of frequency assignment for telecommunication networks. In this model, stations within a given radius r must use frequencies that differ at least by a value p, while stations that are within a larger radius r ′ > r must use frequencies that differ by at least another value q. The aim is to minimize the span of frequencies used in the network. This can be modeled by a graph coloring problem, called the L ( p , q ) labeling, where one wants to label vertices of the graph G modeling the network by integers in the range [ 0 ; M ] , in such a way that: (1) neighbors in G are assigned colors differing by at least p and (2) vertices at distance 2 in G are assigned colors differing by at least q, while minimizing the value of M. M is then called the λ number of G, and is denoted by λ q p ( G ) . In this paper, we study the L ( p , q ) labeling for a specific class of networks, namely the d-dimensional grid G d = G [ n 1 , n 2 , … , n d ] . We give bounds on the value of the λ number of an L ( p , q ) labeling for any d ⩾ 1 and p , q ⩾ 0 . Some of these results are optimal (namely, in the following cases: (1) p = 0 , (2) q = 0 , (3) q = 1 (4) p , q ⩾ 1 , p = α · q with 1 ⩽ α ⩽ 2 d and (5) p ⩾ 2 dq + 1 ); when the results we obtain are not optimal, we observe that the bounds differ by an additive factor never exceeding 2 q - 2 . The optimal result we obtain in the case q = 1 answers an open problem stated by Dubhashi et al. [Channel assignment for wireless networks modelled as d -dimensional square grids, in: Proceedings of the IWDC’02, International Workshop on Distributed Computing, Lecture Notes in Computer Science, vol. 2571, Springer, Berlin, 2002, pp. 130–141], and generalizes results from [A.A Bertossi, C.M. Pinotti, R.B. Tan, Efficient use of radio spectrum in wireless networks with channel separation between close stations, in: Proceedings of the DIAL M for Mobility 2000, Fourth International Workshop on Discrete Algorithms and Methods for Mobile Computing and communications, 2000; A. Dubhashi, S. MVS, A. Pati, S. R., A.M. Shende, Channel assignment for wireless networks modelled as d -dimensional square grids, in: Proceedings of the IWDC’02, International Workshop on Distributed Computing, Lecture Notes in Computer Science, vol. 2571, Springer, Berlin, 2002, pp. 130–141]. We also apply our results to get upper bounds for the L ( p , q ) labeling of d-dimensional hypercubes.

A Prediction-Based Flexible Channel Assignment in Wireless Networks Using Road Topology Information

In this article, a novel prediction technique is proposed, which uses road topology information for prediction. The proposed scheme uses real-time positioning information and road topology information, which matches with the real environment. The scheme uses flexible channel assignment to maintain a better tradeoff between forced termination and call blocking probabilities. For reservation of resources in advance, the information about future handoffs is obtained from the road topology prediction technique. To show the effectiveness of the prediction scheme and flexible channel assignment scheme, this work aims at simulation of other channel assignment strategies—fixed and dynamic channel assignment strategy with and without incorporating the prediction based on road topology information. It gives accurate prediction results, which helps to maintain a better QoS and resource management.

Blocking probability and channel assignment in wireless networks

We consider a multi-hop wireless network with a connection-oriented traffic model and multiple transmission channels that can be spatially re-used. In such a network the blocking probability of a call that makes a channel request depends on (a) the channel assignment scheme and (b) the transmission radius of the nodes which affects the network link structure. In this work, we study these two aspects for simple wireless networks. Specifically, we develop blocking probability analysis for a wireless line and grid network and explore the tradeoff between transmission radius and blocking probability for multi-hop calls. We show that for a line network a larger transmission radius can substantially reduce the blocking probability of calls, while for a grid network with a more dense node topology using a smaller transmission radius is better. We then, investigate various channel assignment schemes and present a novel non-rearranging channel assignment algorithm for multi-hop calls in a general network. Our algorithm efficiently incorporates spatial channel re-use and significantly reduces call blocking probability when compared to other algorithms.

New graph model for channel assignment in ad hoc wireless networks

The channel assignment problem in ad hoc wireless networks is investigated. The problem is to assign channels to hosts in such a way that interference among hosts is eliminated and the total number of channels is minimised. Interference is caused by direct collisions from hosts that can hear each other or indirect collisions from hosts that cannot hear each other, but simultaneously transmit to the same destination. A new class of disk graphs (FDD: interFerence Double Disk graphs) is proposed that include both kinds of interference edges. Channel assignment in wireless networks is a vertex colouring problem in FDD graphs. It is shown that vertex colouring in FDD graphs is NP-complete and the chromatic number of an FDD graph is bounded by its clique number times a constant. A polynomial time approximation algorithm is presented for channel assignment and an upper bound 14 on its performance ratio is obtained. Results from a simulation study reveal that the new graph model can provide a more accurate estimation of the number of channels required for collision avoidance than previous models.

Models and approximation algorithms for channel assignment in radio networks

We consider the frequency assignment (broadcast scheduling) problem for packet radio networks. Such networks are naturally modeled by graphs with a certain geometric structure. The problem of broadcast scheduling can be cast as a variant of the vertex coloring problem (called the distance-2 coloring problem) on the graph that models a given packet radio network. We present efficient approximation algorithms for the distance-2 coloring problem for various geometric graphs including those that naturally model a large class of packet radio networks. The class of graphs considered include (r, s)-civilized graphs, planar graphs, graphs with bounded genus, etc.

Handoff and optimal channel assignment in wireless networks

In this paper, a non-preemptive prioritization scheme for access control in cellular networks is analyzed. Two kinds of users are assumed to compete for the access to the limited number of frequency channels available in each cell: the high priority users represent handoff requests, while the low priority users correspond to initial access requests originated within the same cell. Queueing of handoff requests is also considered. The research for the best access policy is carried out by means of a Markov decision model which allows us to study a very wide class of policies which includes some well known pure stationary policies, as well as randomized ones. The cutoff priority policy, consisting in reserving a certain number of channels to the high priority stream of requests, is proved to be optimal within this class while using an objective function in the form of a linear combination of some quality of service parameters, when no queueing device is considered. Numerical results confirm the optimality of the cutoff priority policy when queueing of handoff requests is allowed.

A unified framework and algorithm for channel assignment in wireless networks

Channel assignment problems in the time, frequency and code domains have thus far been studied separately. Exploiting the similarity of constraints that characterize assignments within and across these domains, we introduce the first unified framework for the study of assignment problems. Our framework identifies eleven atomic constraints underlying most current and potential assignment problems, and characterizes a problem as a combination of these constraints. Based on this framework, we present a unified algorithm for efficient (T/F/C)DMA channel assignments to network nodes or to inter-nodal links in a (multihop) wireless network. The algorithm is parametrized to allow for tradeoff-selectable use as three different variants called RAND, MNF, and PMNF. We provide comprehensive theoretical analysis characterizing the worst-case performance of our algorithm for several classes of problems. In particular, we show that the assignments produced by the PMNF variant are proportional to the thickness of the network. For most typical multihop networks, the thickness can be bounded by a small constant, and hence this represents a significant theoretical result. We also experimentally study the relative performance of the variants for one node and one link assignment problem. We observe that the PMNF variant performs the best, and that a large percentage of unidirectional links is detrimental to the performance in general.