In a wireless network, mobile nodes (MNs) repeatedly perform tasks such as layer 2 (L2) handoff, layer 3 (L3) handoff and authentication. These tasks are critical, particularly for real-time applications such as VoIP. We propose a novel approach, namely Cooperative Roaming (CR), in which MNs can collaborate with each other and share useful information about the network in which they move. We show how we can achieve seamless L2 and L3 handoffs regardless of the authentication mechanism used and without any changes to either the infrastructure or the protocol. In particular, we provide a working implementation of CR and show how, with CR, MNs can achieve a total L2+L3 handoff time of less than 16 ms in an open network and of about 21 ms in an IEEE 802.11i network. We consider behaviors typical of IEEE 802.11 networks, although many of the concepts and problems addressed here apply to any kind of mobile network.
More recently, cooperative approaches have been proposed in the network community. , @cite_2 show how cooperation amongst MNs can be beneficial for all the MNs in the network in terms of bit-rate, coverage and throughput. Each MN builds a table in which possible helpers for that MN are listed. If an MN has a poor link with the AP and its bit-rate is low, it sends packets to the helper who relays them to the AP. The advantage in doing this is that the link from the MN to the helper and from the helper to the AP is a high bit-rate link. In this way the MN can use two high bit-rate links via the helper instead of the low bit-rate one directly to the AP.
@cite_2
2144561012 2129509950 2116820055 2050726943 2044301459 2094000142 2144549564 2211012560 2165715302 2099285351 1968587024 1971045532 2516631548 2159179663 1973089893 2950479988 2149809795 2035307429 2154756494 1552903754
In multiuser MIMO (MU-MIMO) networks, the optimal bit rate of a user is highly dynamic and changes from one packet to the next. This breaks traditional bit rate adaptation algorithms, which rely on recent history to predict the best bit rate for the next packet. To address this problem, we introduce TurboRate, a rate adaptation scheme for MU-MIMO LANs. TurboRate shows that clients in a MU-MIMO LAN can adapt their bit rate on a per-packet basis if each client learns two variables: its SNR when it transmits alone to the access point, and the direction along which its signal is received at the AP. TurboRate also shows that each client can compute these two variables passively without exchanging control frames with the access point. A TurboRate client then annotates its packets with these variables to enable other clients to pick the optimal bit rate and transmit concurrently to the AP. A prototype implementation in USRP-N200 shows that traditional rate adaptation does not deliver the gains of MU-MIMO WLANs, and can interact negatively with MU-MIMO, leading to low throughput. In contrast, enabling MU-MIMO with TurboRate provides a mean throughput gain of 1.7x and 2.3x, for 2-antenna and 3-antenna APs respectively. In wireless local area networks, often a station can potentially associate with more than one access point (AP). Therefore, a relevant question is which AP to select 'best' from a list of candidate ones. In IEEE 802.11, the user simply associates to the AP with the strongest received signal strength. However, this may result in a significant load imbalance between several APs. Moreover, the multi-rate flexibility provided by several IEEE 802.11 variants can cause low bit rate stations to negatively affect high bit rate ones and consequently degrade the overall network throughput. This paper investigates the various aspects of 'best' AP selection for IEEE 802.11 systems. In detail, we first derive a new decision metric which can be used for AP selection. Using this metric, we propose two new selection mechanisms which are decentralised in the sense that the decision is performed by each station, given appropriate status information of each AP. In fact, only few bytes of status information have to be added to the Beacon and Probe Response frames which does not impose significant overhead. We show that our mechanism improves mean quality of service of all stations and better utilises network resources compared to the conventional one implemented today in IEEE 802.11 devices. Also, the schemes are appealing in terms of stability and provide their performance improvement even for denser or lighter network configurations. In this paper, a novel idea of user cooperation in wireless networks has been exploited to improve the performance of the IEEE 802.11 medium access control (MAC) protocol. The new MAC protocol leverages the multi-rate capability of IEEE 802.11b and allows the mobile stations (STA) far away from the access point (AP) to transmit at a higher rate by using an intermediate station as a relay. Two specific variations of the new MAC protocol, namely CoopMAC I and CoopMAC II, are introduced in the paper. Both are able to increase the throughput of the whole network and reduce the average packet delay. Moreover, CoopMAC II also maintains backward compatibility with the legacy 802.11 protocol. The performance improvement is further evaluated by analysis and extensive simulations. The cloud radio access network (C-RAN) concept, in which densely deployed access points (APs) are empowered by cloud computing to cooperatively support mobile users (MUs), to improve mobile data rates, has been recently proposed. However, the high density of active APs results in severe interference and also inefficient energy consumption. Moreover, the growing popularity of highly interactive applications with stringent uplink (UL) requirements, e.g., network gaming and real-time broadcasting by wireless users, means that the UL transmission is becoming more crucial and requires special attention. Therefore in this paper, we propose a joint downlink (DL) and UL MU-AP association and beamforming design to coordinate interference in the C-RAN for energy minimization, a problem which is shown to be NP hard. Due to the new consideration of UL transmission, it is shown that the two state-of-the-art approaches for finding computationally efficient solutions of joint MU-AP association and beamforming considering only the DL, i.e., group-sparse optimization and relaxed-integer programming, cannot be modified in a straightforward way to solve our problem. Leveraging on the celebrated UL-DL duality result, we show that by establishing a virtual DL transmission for the original UL transmission, the joint DL and UL optimization problem can be converted to an equivalent DL problem in C-RAN with two inter-related subproblems for the original and virtual DL transmissions, respectively. Based on this transformation, two efficient algorithms for joint DL and UL MU-AP association and beamforming design are proposed, whose performances are evaluated and compared with other benchmarking schemes through extensive simulations. In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd. (By jointly considering the channel gain and the interference level of the OFDM-based cognitive radio systems, the highest achievable rate of each subchannel can be calculated, which indicates the ability of carrying bits of the subchannel. Using the normalized cost index list, an efficient algorithm is proposed to maximize the sum capacity of the cognitive OFDM systems while keeping the proportional rate constraints satisfied.) This paper studies the newly emerging wireless powered communication network in which one hybrid access point (H-AP) with constant power supply coordinates the wireless energy information transmissions to from a set of distributed users that do not have other energy sources. A "harvest-then-transmit" protocol is proposed where all users first harvest the wireless energy broadcast by the H-AP in the downlink (DL) and then send their independent information to the H-AP in the uplink (UL) by time-division-multiple-access (TDMA). First, we study the sum-throughput maximization of all users by jointly optimizing the time allocation for the DL wireless power transfer versus the users' UL information transmissions given a total time constraint based on the users' DL and UL channels as well as their average harvested energy values. By applying convex optimization techniques, we obtain the closed-form expressions for the optimal time allocations to maximize the sum-throughput. Our solution reveals an interesting "doubly near-far" phenomenon due to both the DL and UL distance-dependent signal attenuation, where a far user from the H-AP, which receives less wireless energy than a nearer user in the DL, has to transmit with more power in the UL for reliable information transmission. As a result, the maximum sum-throughput is shown to be achieved by allocating substantially more time to the near users than the far users, thus resulting in unfair rate allocation among different users. To overcome this problem, we furthermore propose a new performance metric so-called common-throughput with the additional constraint that all users should be allocated with an equal rate regardless of their distances to the H-AP. We present an efficient algorithm to solve the common-throughput maximization problem. Simulation results demonstrate the effectiveness of the common-throughput approach for solving the new doubly near-far problem in wireless powered communication networks. The advantages of coded cooperative data exchange has been studied in the literature. In this problem, a group of wireless clients are interested in the same set of packets (a multicast scenario). Each client initially holds a subset of packets and wills to obtain its missing packets in a cooperative setting by exchanging packets with its peers. Cooperation via short range transmission links among the clients (which are faster, cheaper and more reliable) is an alternative for retransmissions by the base station. In this paper, we extend the problem of cooperative data exchange to the case of multiple unicasts to a set of n clients, where each client c i is interested in a specific message x i and the clients cooperate with each others to compensate the errors occurred over the downlink. Moreover, our proposed method maintains the secrecy of individuals' messages at the price of a substantially small overhead. The issue of routing and maintaining packets between mobile nodes (MNs) in the mobile ad hoc networks (MANETs) has always been a challenge; i.e. encountering broadcast storm under high node density, geographically constrained broadcasting of a service discovery message and local maximum problem under low node density. This requires an efficient design and development of a ‘light-weight’ routing algorithm which can be handled by those GPS equipped devices. Our proposed protocol, Local Area Network Dynamic routing (LANDY) uses a localized routing technique which combines an unique locomotion prediction method and velocity information of MNs to route packets, which is capable of improving the routing performance in advanced mobility scenarios by reducing the control overhead. Simulations have been carried out with randomising the mobility speed and number of nodes and the preliminary results illustrate that LANDY's performance is better compared to other position based routing protocols. In multi-rate wireless LANs, throughput-based fair bandwidth allocation can lead to drastically reduced aggregate throughput. To balance aggregate throughput while serving users in a fair manner, proportional fair or time-based fair scheduling has been proposed to apply at each access point (AP). However, since a realistic deployment of wireless LANs can consist of a network of APs, this paper considers proportional fairness in this much wider setting. Our technique is to intelligently associate users with APs to achieve optimal proportional fairness in a network of APs. We propose two approximation algorithms for periodical offline optimization. Our algorithms are the first approximation algorithms in the literature with a tight worst-case guarantee for the NP-hard problem. Our simulation results demonstrate that our algorithms can obtain an aggregate throughput which can be as much as 2.3 times more than that of the max-min fair allocation in 802.11b. While maintaining aggregate throughput, our approximation algorithms outperform the default user-AP association method in the 802.11b standard significantly in terms of fairness. We consider the distributed uplink resource allocation problem in a multi-carrier wireless network with multiple access points (APs). Each mobile user can optimize its own transmission rate by selecting a suitable AP and by controlling its transmit power. Our objective is to devise suitable algorithms by which mobile users can jointly perform these tasks in a distributed manner. Our approach relies on a game theoretic formulation of the joint power control and AP selection problem. In the proposed game, each user is a player with an associated strategy containing a discrete variable (the AP selection decision) and a continuous vector (the power allocation among multiple channels). We provide characterizations of the Nash Equilibrium of the proposed game. We present a novel algorithm named Joint Access Point Selection and Power Allocation (JASPA) and its various extensions (with different update schedules) that allow the users to efficiently optimize their rates. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations. For the mobile users (MUs) installed with IEEE 802.11 wireless adapters, the default best-signal-strength-based access point (AP) selection is limited since it does not consider fairness and multi-rate issues. In this paper, we propose a distributed AP selection algorithm for newly joining MU and already associated MUs to be adaptive to their joining order and the dynamic wireless environment. We also prove the stability of proposed algorithm and analyze its complexity. Finally, with extensive evaluations, we show that proposed scheme can greatly improve the fairness without significantly sacrificing the efficiency. We investigate an incentive mechanism called Bandwidth Exchange (BE) for cooperative forwarding where transmission bandwidth is used as a flexible resource. We focus on a network where two nodes, communicating with the base station (BS) access point (AP), initially get optimal amount of bandwidth based on direct path transmission and then use their individual bandwidths as flexible incentives for two hop relaying. In our proposed scenario, the forwarder node sends its own data along with the data of the sender in exchange for additional transmission bandwidth, provided by the sender. We compare the performance of the proposed mechanism with optimal bandwidth and power allocation based direct transmission. We use sum rate, max-min rate and min-max power as the evaluation criteria and prove the convex concave nature of the optimization problem formulations. Our numerical analysis shows that the BE based cooperative forwarding extends the coverage in wireless networks when the far node falls in outage under direct transmission. Further, BE significantly improves the max-min rate and min-max power performance of the network. In this paper, we investigate the optimal caching policy, respectively, maximizing the success probability and area spectral efficiency (ASE) in a cache-enabled heterogeneous network (HetNet), where a tier of multi-antenna macro base stations (MBSs) is overlaid with a tier of helpers with caches. Under the probabilistic caching framework, we resort to stochastic geometry theory to derive the success probability and ASE. After finding the optimal caching policies, we analyze the impact of critical system parameters and compare the ASE with traditional HetNet where the MBS tier is overlaid by a tier of pico BSs (PBSs) with limited-capacity backhaul. Analytical and numerical results show that the optimal caching probability is less skewed among helpers to maximize the success probability when the ratios of MBS-to-helper density, MBS-to-helper transmit power, user-to-helper density, or the rate requirement are small, but is more skewed to maximize the ASE in general. Compared with traditional HetNet, the helper density is much lower than the PBS density to achieve the same target ASE. The helper density can be reduced by increasing cache size. With given total cache size within an area, there exists an optimal helper node density that maximizes the ASE. Recent studies demonstrated that dynamic spectrum access can improve spectrum utilization significantly by allowing secondary unlicensed users to dynamically share the spectrum that is not used by the primary licensed users. Cognitive radio was proposed to promote the spectrum utilization by opportunistically exploiting the existence of spectrum "holes." Meanwhile, cooperative relay technology is regarded widely as a key technology for increasing transmission diversity gain in various types of wireless networks, including cognitive radio networks. In this article, we first give a brief overview of the envisioned applications of: cooperative relay technology to CRNs, cooperative transmission of primary traffic by secondary users, cooperative transmission between secondary nodes to improve spatial diversity, and cooperative relay between secondary nodes to improve spectrum diversity. As the latter is a new direction, in this article we focus on this scenario and investigate a simple wireless network, where a spectrum-rich node is selected as the relay node to improve the performance between the source and the destination. With the introduction of cooperative relay, many unique problems should be considered, especially the issue for relay selection and spectrum allocation. To demonstrate the feasibility and performance of cooperative relay for cognitive radio, a new MAC protocol was proposed and implemented in a universal software radio peripheral-based testbed. Experimental results show that the throughput of the whole system is greatly increased by exploiting the benefit of cooperative relay. This paper proposes and experimentally demonstrates a first wireless local area network (WLAN) system that jointly exploits physical-layer network coding (PNC) and multiuser decoding (MUD) to boost system throughput. We refer to this multiple access mode as network-coded multiple access (NCMA). Prior studies on PNC mostly focused on relay networks. NCMA is the first realized multiple access scheme that establishes the usefulness of PNC in a non-relay setting . NCMA allows multiple nodes to transmit simultaneously to the access point (AP) to boost throughput. In the non-relay setting, when two nodes A and B transmit to the AP simultaneously, the AP aims to obtain both packet A and packet B rather than their network-coded packet. An interesting question is whether network coding, specifically PNC which extracts packet @math , can still be useful in such a setting. We provide an affirmative answer to this question with a novel two-layer decoding approach amenable to real-time implementation. Our USRP prototype indicates that NCMA can boost throughput by 100 percent in the medium-high SNR regime ( @math 10 dB). We believe further throughput enhancement is possible by allowing more than two users to transmit together. Consider a scenario of broadcasting a common content to a group of cooperating wireless nodes that are within proximity of each other. Nodes in this group may receive partial content from the source due to packet losses over wireless broadcast links. We further consider that packet losses are different for different nodes. The remaining missing content at each node can then be recovered, thanks to cooperation among the nodes. In this context, the minimum amount of time that can guarantee a complete acquisition of the common content at every node is referred to as the completion time. It has been shown that instantly decodable network coding (IDNC) reduces the completion time as compared to no network coding in this scenario. Yet, for applications such as video streaming, not all packets have the same importance and not all users are interested in the same quality of content. This problem is even more interesting when additional, but realistic constraints, such as strict deadline, bandwidth, or limited energy are added to the problem formulation. We assert that direct application of IDNC in such a scenario yields poor performance in terms of content quality and completion time. In this paper, we propose a novel Content-Aware IDNC scheme that improves content quality and network coding opportunities jointly by taking into account significance of each packet towards the desired quality of service (QoS). Our proposed Content-Aware IDNC maximizes the quality under the completion time constraint, and minimizes the completion time under the quality constraint.We demonstrate the benefits of Content-Aware IDNC through simulations. In this paper, we investigate the effects of “network-level” cooperation in a wireless three-node network with packet erasure links. Cooperation is achieved through the relaying of packets from the node farthest away from the destination by the intermediate node. We consider both scheduled access and random access, and compare the performance metrics of “stability region” and “throughput region”. We observe that the throughput region depends on the priority choices at the relay node, and may or may not be equal to the stability region, which is shown to be independent of the priority choices. By contrast, in the non-cooperative random access system, the stability region and the throughput region are proved to be identical. Furthermore, if we apply network coding at the relay node, there is no improvement either in the stability region or in the throughput region over plain store-and-forward routing. The goal of this paper is to determine the data routes, subchannel schedules, and power allocations that maximize a weighted-sum rate of the data communicated over a generic OFDMA wireless network in which the nodes are capable of simultaneously transmitting, receiving and relaying data. Two instances are considered. In the first instance, subchannels are allowed to be time-shared by multiple links, whereas in the second instance, each subchannel is exclusively used by one of the links. Using a change of variables, the first problem is transformed into a convex form. In contrast, the second problem is not amenable to such a transformation and results in a complex mixed integer optimization problem. To develop insight into this problem, we utilize the first instance to obtain efficiently computable lower and upper bounds on the weighted-sum rate that can be achieved in the absence of time-sharing. Another lower bound is obtained by enforcing the scheduling constraints through additional power constraints and a monomial approximation technique to formulate the design problem as a geometric program. Numerical investigations show that the obtained rates are higher when time-sharing is allowed, and that the lower bounds on rates in the absence of time-sharing are relatively tight. In this paper, a novel cognitive multiple-access strategy in the presence of a cooperating relay is proposed. Exploiting an important phenomenon in wireless networks, source burstiness, the cognitive relay utilizes the periods of silence of the terminals to enable cooperation. Therefore, no extra channel resources are allocated for cooperation and the system encounters no bandwidth losses. Two protocols are developed to implement the proposed multiple-access strategy. The maximum stable throughput region and the delay performance of the proposed protocols are characterized. The results reveal that the proposed protocols provide significant performance gains over conventional relaying strategies such as selection and incremental relaying, specially at high spectral efficiency regimes. The rationale is that the lossless bandwidth property of the proposed protocols results in a graceful degradation in the maximum stable throughput with increasing the required rate of communication. On the other hand, conventional relaying strategies suffer from catastrophic performance degradation because of their inherent bandwidth inefficiency that results from allocating specific channel resources for cooperation at the relay. The analysis reveals that the throughput region of the proposed strategy is a subset of its maximum stable throughput region, which is different from random access, where both regions are conjectured to be identical. Mobile data offloading through complementary network technologies such as WiFi and femtocell can significantly alleviate network congestion and enhance users' QoS. In this paper we consider a market where mobile network operators (MNOs) lease third-party deployed WiFi or femtocell access points (APs) to dynamically offload the traffic of their mobile users. We assume that each MNO can employ multiple APs and each AP can concurrently serve traffic from multiple MNOs. We design an iterative double auction mechanism that ensures the efficient operation of the market, where MNOs maximize their offloading benefits and APs minimize their offloading costs. Such a mechanism incorporates the special characteristics of the wireless network, such as the coupling of MNOs' offloading decisions and APs' capacity constraints. The proposed market scheme does not require full information about the MNOs and APs, incurs minimum communication overhead, and creates non-negative revenue for the market broker.