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Molisch, “Fast multiple access selection through variable power transmission,” in preparation
"... Many wireless applications demand a fast mechanism to detect the packet from a node with the highest priority (”best node”) only, while packets from nodes with lower priority are irrelevant. In this paper, we introduce an extremely fast contentionbased multiple access algorithm that selects the bes ..."
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Cited by 14 (10 self)
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Many wireless applications demand a fast mechanism to detect the packet from a node with the highest priority (”best node”) only, while packets from nodes with lower priority are irrelevant. In this paper, we introduce an extremely fast contentionbased multiple access algorithm that selects the best node and requires only local information of the priorities of the nodes. The algorithm, which we call Variable Power Multiple Access Selection (VPMAS), uses the local channel state information from the accessing nodes to the receiver, and maps the priorities onto the receive power. It is based on a key result that shows that mapping onto a set of discrete receive power levels is optimal, when the power levels are chosen to exploit packet capture that inherently occurs in a wireless physical layer. The VPMAS algorithm adjusts the expected number of users that contend in each step and their respective transmission powers, depending on whether previous transmission attempts resulted in capture, idle channel, or collision. We also show how reliable information regarding the total received power at the receiver can be used to improve the algorithm by enhancing the feedback mechanism. The algorithm detects the packet from the best node in 1.5 to 2.1 slots, which is considerably lower than the 2.43 slot average achieved by the best algorithm known to date.
1Optimal Routing with Mutual Information Accumulation in Wireless Networks
"... Abstract—We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest ..."
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Cited by 4 (0 self)
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Abstract—We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path routing. Further, it also outperforms cooperative communication techniques that are based on energy accumulation. However, it requires complex and combinatorial networking decisions concerning which nodes participate in transmission, and which decode ordering to use. We formulate three problems of interest in this setting: (i) minimum delay routing, (ii) minimum energy routing subject to delay constraint, and (iii) minimum delay broadcast. All of these are hard combinatorial optimization problems and we make use of several structural properties of their optimal solutions to simplify the problems and derive optimal greedy algorithms. Although the reduced problems still have exponential complexity, unlike prior works on such problems, our greedy algorithms are simple to use and do not require solving any linear programs. Further, using the insight obtained from the optimal solution to a line topology, we propose two simple heuristics that can be implemented in polynomial time and in a distributed fashion and compare them with the optimal solution. Simulations suggest that both heuristics perform very close to the optimal solution over random network topologies.
Performance of a Fast, Distributed Multiple Access Based Relay Selection Algorithm Under Imperfect Statistical Knowledge
"... Abstract—Cooperative wireless systems can exploit spatial diversity by opportunistically selecting the best relay to forward data to a destination. However, determining the best relay is a challenging task and requires a selection algorithm because the relays are geographically separated and only ha ..."
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Cited by 1 (1 self)
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Abstract—Cooperative wireless systems can exploit spatial diversity by opportunistically selecting the best relay to forward data to a destination. However, determining the best relay is a challenging task and requires a selection algorithm because the relays are geographically separated and only have local channel knowledge. Selecting the best relay is equivalent to finding the relay with the largest metric, where each relay computes its metric using local channel knowledge. We analyze the performance of a fast, distributed, and scalable multiple access based selection algorithm when it assumes incorrect values for two fundamental parameters that it requires to operate efficiently – the number of available relays and the cumulative distribution function (CDF) of the metrics. Such imperfect knowledge will invariably arise in practice. We develop new expressions for the time required to select the best relay as a function of the assumed and actual parameters. We show that imperfect knowledge can significantly slow down the selection algorithm. Further, in a system that uses its observations to update its CDF estimate, we determine the minimum number of observations required to limit the performance degradation. We also develop a minimax formulation that makes the algorithm robust to uncertainties in the number of relays in the system. Index Terms—Multiple access techniques, relays, cooperative communications, splitting algorithms, diversity, selection, crosslayer optimization, distributed, estimation. I.
Networks
, 2006
"... This paper considers a sensor network where relay nodes cooperate in order to minimize the total energy consumption for the unicast transmission of a message from a single source to a single destination. We assume Destination Energy Accumulation, i.e., the destination can accumulate the energy of mu ..."
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This paper considers a sensor network where relay nodes cooperate in order to minimize the total energy consumption for the unicast transmission of a message from a single source to a single destination. We assume Destination Energy Accumulation, i.e., the destination can accumulate the energy of multiple copies of the message, each of which is too weak to be reliably decoded by itself, while the relay nodes use a decodeandforward approach. We propose the Progressive Accumulative Routing (PAR) algorithm, which performs relay discovery, relay ordering and power allocation in a distributed manner so that each relay node only needs information about its neighboring nodes. Simulations verify that the algorithm considerably reduces the total energy consumption, and can be implemented efficently. Furthermore, it performs close to the optimal DEA route with high probability.
Optimal Routing with Mutual Information 1 Accumulation in Wireless Networks
"... We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path rou ..."
Abstract
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We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path routing. Further, it also outperforms cooperative communication techniques that are based on energy accumulation. However, it creates complex and combinatorial networking decisions concerning which nodes participate in transmission, and which decode ordering to use. We formulate three problems of interest in this setting: (i) minimum delay routing, (ii) minimum energy routing subject to delay constraint, and (iii) minimum delay broadcast. All of these are hard combinatorial optimization problems and we make use of several structural properties of their optimal solutions to simplify the problems and derive optimal greedy algorithms. Although the reduced problems still have exponential complexity, unlike prior works on such problems, our greedy algorithms are simple to use and do not require solving any linear programs. Further, using the insight obtained from the optimal solution to a linear network, we propose two simple heuristics that can be implemented in polynomial time in a distributed fashion and compare them with the optimal solution. Simulations suggest that both heuristics perform very close to the optimal solution over random network topologies.
Progressive Accumulative Routing in Wireless
, 2006
"... This paper considers a sensor network where relay nodes cooperate in order to minimize the total energy consumption for the unicast transmission of a message from a single source to a single destination. We assume Destination Energy Accumulation, i.e., the destination can accumulate the energy of mu ..."
Abstract
 Add to MetaCart
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This paper considers a sensor network where relay nodes cooperate in order to minimize the total energy consumption for the unicast transmission of a message from a single source to a single destination. We assume Destination Energy Accumulation, i.e., the destination can accumulate the energy of multiple copies of the message, each of which is too weak to be reliably decoded by itself, while the relay nodes use a decodeandforward approach. We propose the Progressive Accumulative Routing (PAR) algorithm, which performs relay discovery, relay ordering and power allocation in a distributed manner so that each relay node only needs information about its neighboring nodes. Simulations verify that the algorithm considerably reduces the total energy consumption, and can be implemented efficently. Furthermore, it performs close to the optimal DEA route with high probability.