Signal To Interference Plus Noise Ratio Model Research Articles

A maximum clique based approximation algorithm for wireless link scheduling under SINR model

In this paper, we focus on the shortest link scheduling (SLS) in wireless networks under the Signal-to-Interference-plus-Noise-Ratio (SINR) constraints. We introduce a consistent graph G¯=(V¯,E¯) where V¯ is the links set and each edge in E¯ indicates that its two ends can be active simultaneously. We interpret SLS as the finding of a clique partition in G¯ and propose a fast approximation algorithm, MCBS (Maximum Clique Based Scheduling), for SLS with a uniform power assignment and with an approximation ratio to the optimal solution of O(1). Theoretical analysis demonstrates the correctness and effectiveness of the proposed algorithm. Our simulation results show that the MCBS algorithm overcomes the best known algorithms in terms of execution time and the number of time slots.

Practical Network Conditions for the Convergence of Distributed Optimization

The decentralized nature of multi-agent learning often requires continuous information exchange over a (wireless) communication network, in order to accomplish common global objectives. Uncertainty and delay in communication induce large Age of Information (AoI) for data available at the agents, possibly affecting algorithm performance. In order to understand this, one needs communication models that are representative of practical wireless networks. In this paper, we present a representative model based on the Signal-to-Interference-plus-Noise Ratio (SINR) between pairs of agents. Further, we present a novel medium access control (MAC) protocol that is sensitive to local AoI. Our SINR model facilitates the representation of practical dependency effects like shadowing, fading, interference and external noise. The model is driven by an underlying geometrically ergodic Markov chain, which can represent agent mobility. Our MAC protocol enables that the aforementioned dependency effects decay over time. With this dependency decay, we then control the asymptotic growth of the AoI, to facilitate the convergence of distributed algorithms. Finally, we illustrate our ideas by analyzing the distributed stochastic gradient descent scheme that uses delayed communicated data.

Shortest link scheduling in wireless networks with oblivious power control

Link scheduling has always been a fundamental problem in wireless networks for its direct impacts on the performance of wireless networks such as throughput capacity, transmission delay, lifetime, etc. Existing work is mainly established under graph-based models, which are not only impractical but also incorrect due to the essentially fading characteristics of signals. In this paper, we study the shortest link scheduling problem under two more realistic models, namely the signal to interference plus noise ratio (SINR) model and the Rayleigh fading model. We propose a centralized square-based scheduling algorithm (CSSA) with oblivious power control under the SINR model and prove its correctness under both the SINR model and the Rayleigh fading model. Furthermore, we extend CSSA and propose a distributed square-based scheduling algorithm (DSSA). Note that DSSA adopts CSMA/CA so that a wireless node can compete for the wireless channel before starting its communication. We also show theoretical analysis and conduct extensive simulations to exhibit the correctness and efficiency of our algorithms.

Distributed Stable Global Broadcasting for SINR-Based Multi-Channel Wireless Multi-Hop Networks

Recently, the problem of Stable Global Broadcasting (SGB) with continuous packet injections at a source node has attracted considerable attention and much work has been carried out. However, existing SGB algorithms are all centralized and under the graph-based interference model. How to achieve efficient distributed SGB under the more realistic Signal-to-Interference-plus-Noise-Ratio (SINR) interference model is still an open issue. In this paper, we focus on the design of distributed SGB algorithms for multi-channel wireless multi-hop networks under the SINR model. We first present an efficient Backbone-based Multi-channel Concurrent Scheduling (BMCS) strategy and prove an upper bound of $1/2$ packets/slot for the broadcast capacity (i.e., the maximum supportable packet injection rate for all possible SGB algorithms). By iterating the BMCS strategy in different ways, we present two distributed SGB algorithms, one for deterministic packet injection model corresponding to the broadcast capacity (called SGB-DPI) and another for stochastic packet injection model (called SGB-SPI). We prove that: 1) both SGB-DPI and SGB-SPI meet the queue stability and latency stability constraints for providing stable global broadcasting services, and 2) SGB-DPI is throughput-optimal. We evaluate the performance of our proposed algorithms through simulations. The simulation results validate our theoretical analysis and also show that even under the stochastic packet injection model, SGB-DPI has a comparable and even better throughput performance than SGB-SPI.

Deterministic protocols in the SINR model without knowledge of coordinates

This work studies multi-broadcasting for the SINR (Signal-to-Interference-plus-Noise-Ratio) model, assuming a subset of nodes are initially awake, when each device only has access to knowledge about the total number of nodes in the network n, the range from which each node's label is taken {1,…,N}, and the label of the device itself. We assume no knowledge of the physical coordinates of devices and no knowledge of the neighborhood of each node. We present a deterministic protocol for this problem that runs in O(nlg⁡Nlg⁡n) rounds. There is no known polytime deterministic algorithm for this setting. A lower bound of Ω(nlg⁡N) rounds is known for deterministic broadcasting without local knowledge [30]. We also present algorithms to achieve multi-broadcast in O(nlg⁡N) rounds and create a backbone in O(nlg⁡N) rounds, assuming that all nodes are initially awake.

Power-efficient and interference-free link scheduling algorithms for connected wireless sensor networks

A fundamental aspect in performance engineering of wireless sensor networks (WSN) is optimizing the set of links that can be concurrently activated to meet a given signal-to-interference-plus-noise ratio (SINR) threshold. The solution of this combinatorial problem is a key element in wireless link scheduling. Another key architectural goal in WSN is connectivity. The connectivity of sensor nodes is critical for WSN, as connected graphs can be used for both data collection and data dissemination. In this paper, we investigate the joint scheduling and connectivity problem in WSN assuming the SINR model. We propose algorithms to build connected communication graphs with power-efficient links to be scheduled simultaneously in one time slot. The algorithms aiming at minimizing the number of time slots needed to successfully schedule all the given links such that the nodes can communicate without interference in the SINR model. While power-efficient and interference-free schedules reduce energy consumption, minimization of the schedule length (shortest link scheduling) has the effect of maximizing network throughput. We propose one greedy randomized constructive heuristic, two local search procedures, and three greedy randomized adaptive search procedures metaheuristics. We report computational experiments comparing the effectiveness of the proposed algorithms. Our simulation also shows the trade-off between power consumption and schedule length and the results indicate that not only the overall performance of our algorithms, but also show that the total power and schedule length value of its solutions are better than the existing work.

Leader election in SINR model with arbitrary power control

We consider the Leader Election Problem in the Signal-to-Interference-plus-Noise-Ratio (SINR) model where nodes can adjust their transmission power. We show that in this setting it is possible to elect a leader in two communication rounds, with high probability. Previously, it was known that Θ(log⁡n) rounds were sufficient and necessary when using uniform power, where n is the number of nodes in the network.We then examine how much power control is needed to achieve fast leader election. We show that every 2-round leader election algorithm in the SINR model running correctly w.h.p. requires a power range 2Ω(n), even when n is known. We complement this with an algorithm that uses power range 2O˜(n)1, when n is known, and 2O˜(n1.5), when n is not known. We also explore tradeoffs between time and power used, and show that to elect a leader in t rounds, a range of possible power levels of size exp(n1/Θ(t)) is sufficient and necessary.

Shortest Link Scheduling Algorithms in Wireless Networks Under the SINR Model

This paper considers the shortest link scheduling problem in wireless networks under the signal-to-interferenceplus-noise ratio(SINR) model.We propose an O(log(l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> /l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> ))approximation algorithm called shortest link scheduling with power control (SLSPC) with oblivious power assignment and an O(log <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1+φ</sub> (l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> /l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> )-approximation algorithm called shortest link scheduling with uniform or mean power assignment (SLSUM) with uniform or mean power control, where φ > 0 is a constant serving as a regulatory factor for slight transmit power adjustment, and where l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> and l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> denote the lengths of the longest and shortest links, respectively. We conduct a rigorous theoretical performance analysis to analyze the feasibility and approximation factors of the proposed algorithms. We also carry out an extensive comparison-based simulation study, whose results indicate that the performances of SLSPC and SLSUM are superior over the state of the art as the set of the so-called “black and gray” links, which are difficult to schedule and should be sequentially scheduled, is completely removed by adjusting the transmit power appropriately via φ. Our numerical analysis demonstrates that the approximation ratios of our algorithms are tighter than the best known ratios.

SINR based shortest link scheduling with oblivious power control in wireless networks

In this paper, we consider shortest link scheduling (SLS), a fundamental problem in wireless networks to improve the network performance, under the signal-to-interference-plus-noise-ratio (SINR) constraints. It is challenging to design efficient SLS algorithms due to the intrinsic non-locality of SINR. However, if two transmission links are far away from each other, the interference of one link on the other should be small under the SINR model. This motivates us to consider the interference only in a local area, which decreases the difficulty of designing link scheduling under SINR, by partitioning the links into disjoint local link sets with a certain distance away from each other, such that independent scheduling inside each local link set is possible. Based on this idea, we propose a novel approximation algorithm PPSLS (Plane Partition based Shortest Link Scheduling) for SLS with oblivious power control. Theoretical analysis and simulations demonstrate the correctness and effectiveness of the proposed algorithm.

On the power of uniform power: capacity of wireless networks with bounded resources

The throughput capacity of arbitrary wireless networks under the physical Signal to Interference Plus Noise Ratio (SINR) model has received much attention in recent years. In this paper, we investigate the question of how much the worst-case performance of uniform and non-uniform power assignments differ under constraints such as a bound on the area where nodes are distributed or restrictions on the maximum power available. We determine the maximum factor by which a non-uniform power assignment can outperform the uniform case in the SINR model. More precisely, we prove that in one-dimensional settings the capacity of a non-uniform assignment exceeds a uniform assignment by at most a factor of O(logL max ) when the length of the network is L max . In two-dimensional settings, the uniform assignment is at most a factor of O(logP max ) worse than the non-uniform assignment if the maximum power is P max . We provide algorithms that reach this capacity in both cases. Due to lower bound examples in previous work, these results are tight in the sense that there are networks where the lack of power control causes a performance loss in the order of these factors. As a consequence, engineers and researchers may prefer the uniform model due to its simplicity if this degree of performance deterioration is acceptable.

Heuristic Algorithms for One-Slot Link Scheduling in Wireless Sensor Networks under SINR

One-slot link scheduling is important for enhancing the throughput capacity of wireless sensor networks. It includes two aspects: maximum links scheduling (MLS) and maximum weighted links scheduling (MWLS). In this paper we propose two heuristic algorithms for the two NP-hard problems with obvious power assignments under the SINR (signal-to-interference-plus-noise-ratio) model. For MLS, we propose an algorithm MTMA (maximum tolerance and minimum affectance), which improves the currently best approximation algorithm by 28%–62% on average. For MWLS, we give an effective heuristic algorithm MWMA (maximum weighted and minimum affectance), which performs better on improving the throughput and reducing the running time. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations.

Distributed Link Scheduling Under SINR Model in Multihop Wireless Networks

Link adaptation technologies, such as Adaptive Modulation and Coding (AMC) and Multiple-Input-Multiple-Output (MIMO), are used in advanced wireless communication systems to achieve high spectrum efficiency. Communication performance can be improved significantly by adaptive transmissions based on the quality of received signals, i.e., the signal-to-interference-plus-noise ratio (SINR). However, for multihop wireless communications, most link scheduling schemes have been developed under simplified interference models that do not account for accumulative interference and cannot fully exploit the recent advances in PHY-layer communication theory. This paper focuses on developing link scheduling schemes that can achieve optimal performance under the SINR model. One key idea is to treat an adaptive wireless link as multiple parallel virtual links with different signal quality, building on which we develop throughput-optimal scheduling schemes using a two-stage queueing structure in conjunction with recently developed carrier-sensing techniques. Furthermore, we introduce a novel three-way handshake to ensure, in a distributed manner, that all transmitting links satisfy their SINR requirements. We evaluate the proposed schemes through rigorous analysis and simulations.

Minimum Latency Broadcast in the SINR Model: A Parallel Routing and Scheduling Approach

We study the minimum latency data broadcast problem under the signal-to-interference-plus-noise-ratio (SINR) model, which is known to capture wireless interference more accurately and realistically than the widely used graph-based models. Previous work mainly involves building a broadcast tree first and then computing interference-aware TDMA schedules for the links on the tree. Observing that the separation of routing and scheduling may lead to unsaturated transmissions in each time slot, we develop a polynomial-time heuristic algorithm, namely PRS, by advocating a parallel way of constructing routing and transmission schedules. Theoretical analysis indicates that PRS generates correct schedules under the SINR constraints. Simulation results demonstrate that PRS outperforms state-of-the-art algorithms in terms of broadcast latency under various network conditions.

Distributed CSMA Algorithms for Link Scheduling in Multihop MIMO Networks Under SINR Model

In this paper, we study distributed scheduling in multihop multiple-input-multiple-output (MIMO) networks. We first develop a model that provides the upper layers a set of rates and signal-to-interference-plus-noise ratio (SINR) requirements that capture the rate-reliability tradeoff in MIMO communications. The main thrust of this paper is then dedicated to developing distributed carrier sense multiple access (CSMA) algorithms for MIMO-pipe scheduling under the SINR interference model. We choose the SINR model over the extensively studied protocol-based interference models because it more naturally captures the impact of interference in wireless networks. The coupling among the links caused by the interference under the SINR model makes the problem of devising distributed scheduling algorithms very challenging. To that end, we explore the CSMA algorithms for MIMO-pipe scheduling from two perspectives. We start with an idealized continuous-time CSMA network, where control messages can be exchanged in a collision-free manner, and devise a CSMA-based link scheduling algorithm that can achieve throughput optimality under the SINR model. Next, we consider a discrete-time CSMA network, where the message exchanges suffer from collisions. For this more challenging case, we develop a scheduling algorithm by imposing a more stringent SINR constraint on the MIMO-pipe model. We show that the proposed conservative scheduling achieves an efficiency ratio bounded from below.

Interference Pricing for SINR-Based Random Access Game

In this paper, we study the problem of random access with interference pricing in wireless ad hoc networks using non-cooperative game theory. While most of the previous works in random access games are based on the protocol model, we analyze the game under the more accurate signal-to-interference-plus-noise-ratio (SINR) model. First, under the setting with fixed interference linear pricing, we characterize the existence of the Nash equilibrium (NE) in the random access game. In particular, when the utility functions of all the players satisfy a risk aversion condition, we show that the game is a S-modular game and characterize the convergence of the strategy profile to the NE. Then, under the setting with adaptive interference linear pricing, we propose an iterative algorithm that aims to solve the network utility maximization (NUM) problem. Convergence of the solution to a Karush-Kuhn-Tucker (KKT) point of the NUM problem is studied. It can be shown that the solution obtained under the protocol model may result in starvation for some users due to the inaccurate interference pricing. Simulation results show that our proposed algorithm based on the SINR model achieves a higher average utility than the algorithm based on the protocol model and a carrier sense multiple access (CSMA) scheme implemented in a slotted time system.

SINR-Based Random Access for Cognitive Radio: Distributed Algorithm and Coalitional Game

In this paper, we study the problem of multi-channel medium access control (MAC) in cognitive radio (CR) networks. While most of the previously proposed MAC protocols for CR networks are heuristic and are based on the simplistic protocol model, we design a distributed MAC protocol using the more accurate signal-to-interference-plus-noise-ratio (SINR) model. First, we assume that the secondary users are cooperative and formulate the problem of assigning transmission and listening probabilities for random access as a non-convex network utility maximization problem. We propose a three-phase algorithm that converges to a near-optimal solution after solving a number of convex optimization problems distributively. Simulation results show that our proposed algorithm based on the SINR model achieves a higher aggregate throughput than other schemes which are based on the protocol model. Then, we consider the case that the secondary users are rational. We use coalitional game theory to study the incentive issues of user cooperation in a given channel for the SINR model. In particular, we use the solution concept of the core to analyze the stability of the grand coalition, and the solution concept of the Shapley value to fairly divide the payoff among the users. We show that the Shapley value lies in the core when all the users are one-hop neighbours of each other. We illustrate the Shapley value and the core with a numerical example.

Capacity of wireless networks under SINR interference constraints

A fundamental problem in wireless networks is to estimate their throughput capacity--given a set of wireless nodes and a set of connections, what is the maximum rate at which data can be sent on these connections. Most of the research in this direction has focused either on random distributions of points, or has assumed simple graph-based models for wireless interference. In this paper, we study the capacity estimation problem using a realistic Signal to Interference Plus Noise Ratio (SINR) model for interference, on arbitrary wireless networks without any assumptions on node distributions. The problem becomes much more challenging for this setting, because of the non-locality of the SINR model. Recent work by Moscibroda et al. (IEEE INFOCOM 2006, ACM MobiHoc 2006) has shown that the throughput achieved by using SINR models can differ significantly from that obtained by using graph-based models. In this work, we develop polynomial time algorithms to provably approximate the throughput capacity of wireless network under the SINR model.

Broadcast Scheduling in Interference Environment

Broadcast is a fundamental operation in wireless networks and naive flooding is not practical because it cannot deal with interference. Scheduling is a good way to avoid interference, but previous studies on broadcast scheduling algorithms all assume highly theoretical models such as the unit disk graph model. In this work, we re-investigate this problem using the 2-disk and the signal-to-interference-plus-noise-ratio (SINR) model to realize it. We first design a constant approximation algorithm for the 2-disk model and then extend it to the SINR model. This result is the first result on broadcast scheduling algorithms in SINR model, to the best of our knowledge.