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Distributed MultiInterface MultiChannel Random Access Using Convex Optimization
"... Abstract—The aggregate capacity of wireless adhoc networks can be increased substantially if each node is equipped with multiple network interface cards (NICs) and each NIC operates on a distinct frequency channel. Most of the recently proposed channel assignment algorithms are based on combinatori ..."
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Abstract—The aggregate capacity of wireless adhoc networks can be increased substantially if each node is equipped with multiple network interface cards (NICs) and each NIC operates on a distinct frequency channel. Most of the recently proposed channel assignment algorithms are based on combinatorial techniques. Combinatorial channel assignment schemes may sometimes result in computationally complicated algorithms as well as inefficient utilization of the available frequency spectrum. In this paper, we analytically model channel and interface assignment problems as tractable continuous optimization problems within the framework of network utility maximization (NUM). In particular, the link data rate models for both singlechannel reception and multichannel reception scenarios are derived. The assignment of both nonoverlapped and partiallyoverlapped channels are also considered. We then propose two distributed multiinterface multichannel random access (DMMRA) algorithms for singlechannel reception and multichannel reception scenarios. The DMMRA algorithms are fast, distributed, and easy to implement. Each algorithm solves the formulated NUM problem for each scenario. DMMRA requires each node to only iteratively solve a local, myopic, and convex optimization problem. Convergence and optimality properties of our algorithms are studied analytically. Simulation results show that our proposed algorithms significantly outperform utilityoptimal combinatorial channel assignment algorithms in terms of both achieved network utility and throughput. Index Terms—Multiinterface multichannel wireless adhoc networks, random access, persistent probabilities, network utility maximization, convex optimization, singlechannel reception, multichannel reception, partially overlapped frequency channels. F 1
Resource Allocation for CrossLayer Utility Maximization in MultiHop Wireless Networks in the Presence of Self Interference
, 2010
"... The crosslayer utility maximization problem subject to stability constraints is considered for a multihop wireless network. A time slotted network, where the channel gains are changing randomly from slot to slot is assumed. The optimal crosslayer network control policy can be decomposed into thr ..."
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The crosslayer utility maximization problem subject to stability constraints is considered for a multihop wireless network. A time slotted network, where the channel gains are changing randomly from slot to slot is assumed. The optimal crosslayer network control policy can be decomposed into three subproblems: 1) flow control, 2) nexthop routing and innode scheduling, and 3) power and rate control, also known as resource allocation (RA). In the case of multihop networks, RA subproblem is particularly difficult to solve due to the self interference problem which arises when a node simultaneously transmits and receives in the same channel. According to relative distances between networks nodes, the self interference coefficients can be several order of magnitude larger than the power gains between distinct nodes. Thus, standard RA methods for bipartite networks can not be applied directly. The main contribution of this paper is to derive a novel RA algorithm for multihop wireless networks which is capable to deal with the self interference problem and does not rely on combinatorial constraints for finding the set of links which can be simultaneously activated. The numerical results show that the proposed RA algorithm can provide significant gains at network layer in terms of endtoend rates and network congestion, even though the solution is local.
Bandwidth and Transmit Power Allocation for QoS Support in Wireless Networks
"... Abstract — With the continued increase of speed and capacities of computing devices and the growing needs of people for mobile computing capabilities, allocation of resource plays a vital role in research community. Quality of service (QoS) provisioning in MANETs is an essential component needed to ..."
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Abstract — With the continued increase of speed and capacities of computing devices and the growing needs of people for mobile computing capabilities, allocation of resource plays a vital role in research community. Quality of service (QoS) provisioning in MANETs is an essential component needed to support multimedia and realtime applications. Maximizing the utility of the traffic flow is a challenging problem. To overcome this problem a new framework was designed. This framework achieves the maximum utility of the flow by considering Channels, Transmission power levels and Bandwidth as the parameter. The framework uses two methods. One is cross decomposition approach to overcome the problem due to selfinterference of the packets. We build admission control along with this method which avoids congestion in network by only admitting requests which do not cause self interference. This cross decomposition approach compared with Utility based allocation to find the optimal solution. This algorithms act as designing guidelines for resource allocation of QoS traffic in a wireless network, which take into account the total available resource of network, the users ’ traffic characteristics, and the users ’ channel qualities. This work focuses the resource allocation in terms of Channels, Transmission power and bandwidth. A comparison between both the methods is also performed.