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The capacity of wireless networks
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2000
"... When n identical randomly located nodes, each capable of transmitting at bits per second and using a fixed range, form a wireless network, the throughput @ A obtainable by each node for a randomly chosen destination is 2 bits per second under a noninterference protocol. If the nodes are optimally p ..."
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When n identical randomly located nodes, each capable of transmitting at bits per second and using a fixed range, form a wireless network, the throughput @ A obtainable by each node for a randomly chosen destination is 2 bits per second under a noninterference protocol. If the nodes are optimally placed in a disk of unit area, traffic patterns are optimally assigned, and each transmission’s range is optimally chosen, the bit–distance product that can be transported by the network per second is 2 @ A bitmeters per second. Thus even under optimal circumstances, the throughput is only 2 bits per second for each node for a destination nonvanishingly far away. Similar results also hold under an alternate physical model where a required signaltointerference ratio is specified for successful receptions. Fundamentally, it is the need for every node all over the domain to share whatever portion of the channel it is utilizing with nodes in its local neighborhood that is the reason for the constriction in capacity. Splitting the channel into several subchannels does not change any of the results. Some implications may be worth considering by designers. Since the throughput furnished to each user diminishes to zero as the number of users is increased, perhaps networks connecting smaller numbers of users, or featuring connections mostly with nearby neighbors, may be more likely to be find acceptance.
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"... Queuing aspects of multiantenna multiple access channels Abstract — In this communication, we investigate the effect of spatial dimension in a Gaussian multiple access system and study its impact on the physical layer capacity and the end to end delay from a queueing theory perspective. For a multip ..."
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Queuing aspects of multiantenna multiple access channels Abstract — In this communication, we investigate the effect of spatial dimension in a Gaussian multiple access system and study its impact on the physical layer capacity and the end to end delay from a queueing theory perspective. For a multipleinput, singleoutput (MISO) multiple access channel, we derive conditions on the transmit power and number of transmit antennas for which additional users increase or decrease the capacity. The capacity as a function of the number of users is used for calculating the endtoend delay. Numerical analysis on the endtoend delay for a Rayleigh fading MISO channel with no channel state information at transmitter (CSIT) indicates that increasing the number of transmit antennas can actually increase the delay! Index terms – MIMO, MAC, Queueing theory I.
Power efficient scheduling in multihop networks
"... In this paper, we present schedulers that minimize the total transmit power in a multihop wireless network. The focus is on guaranteeing an endtoend delay bound for a single variable bit rate flow on a multihop fading channel. We first compute an analytical approximation for the transmit power req ..."
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In this paper, we present schedulers that minimize the total transmit power in a multihop wireless network. The focus is on guaranteeing an endtoend delay bound for a single variable bit rate flow on a multihop fading channel. We first compute an analytical approximation for the transmit power required to send a variable bit rate source over a finite state fading channel. We then use this approximation to derive schedulers that have low complexity and near optimal performance over multihop networks where the fading processes on the multiple hops are independent. Properties of the optimal delay allocation are also studied; in the special case of a Gaussian network, the optimal delay allocation strategy is completely characterized.
Research Article Exploiting Transmit Buffer Information at the Receiver in BlockFading Channels
"... It is well known that channel state information at the transmitter (CSIT) leads to higher throughput in fading channels. We motivate the use of transmit buffer information at receiver (TBIR). The thesis of this paper is that having partial or complete instantaneous TBIR leads to a lower packet loss ..."
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It is well known that channel state information at the transmitter (CSIT) leads to higher throughput in fading channels. We motivate the use of transmit buffer information at receiver (TBIR). The thesis of this paper is that having partial or complete instantaneous TBIR leads to a lower packet loss rate in blockfading channels assuming the availability of partial CSIT. We provide a framework for the joint design and analysis of feedback (FB) and feedforward (FF) information in fading channels. We then introduce two forms of TBIR—statistical and instantaneous—and show the gains of each form of TBIR using a heuristic scheme. For a Rayleigh fading channel, we show that in certain cases the packet error rate reduces by nearly an order of magnitude with just one bit of feedforward information of TBIR. Copyright © 2009 Dinesh Rajan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
Power Efficient Delay Allocation in Multihop Wireless Networks
"... Abstract—In this paper, we present delay allocation strategies that minimize the total transmit power in a multihop wireless network. The focus is on guaranteeing an endtoend average delay bound for a single variablebitrate flow on a multihop fading channel. We first compute an analytical approx ..."
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Abstract—In this paper, we present delay allocation strategies that minimize the total transmit power in a multihop wireless network. The focus is on guaranteeing an endtoend average delay bound for a single variablebitrate flow on a multihop fading channel. We first compute an analytical approximation for the transmit power that is required to send a variablebitrate source over a finitestate fading channel. We then use this approximation to derive a lowcomplexity and nearoptimal delay allocation method for multihop networks when the fading processes on the multiple hops are independent. Properties of the optimal delay allocation are also studied; in the special case of a Gaussian network, the optimal delay allocation strategy is completely characterized. The tradeoff between singlehop transmission and multihop transmission is studied under an endtoend delay constraint. Index Terms—Delay guarantees, multihop, queuing, scheduling, wireless network.