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Previous research on sensor network security mainly considers homogeneous sensor networks, where all sensor nodes have the same capabilities. Research has shown that homogeneous ad hoc networks have poor performance and scalability. The many-to-one traffic pattern dominates in sensor networks, and hence a sensor may only communicate with a small portion of its neighbors. Key management is a fundamental security operation. Most existing key management schemes try to establish shared keys for all pairs of neighbor sensors, no matter whether these nodes communicate with each other or not, and this causes large overhead. In this paper, we adopt a Heterogeneous Sensor Network (HSN) model for better performance and security. We propose a novel routing-driven key management scheme, which only establishes shared keys for neighbor sensors that communicate with each other. We utilize Elliptic Curve Cryptography in the design of an efficient key management scheme for sensor nodes. The performance evaluation and security analysis show that our key management scheme can provide better security with significant reductions on communication overhead, storage space and energy consumption than other key management schemes.

Device placement is a fundamental factor in determining the coverage, connectivity, cost and lifetime of a wireless sensor network (WSN). In this paper, we explore the problem of relay node placement in heterogeneous WSN. We formulate a generalized node placement optimization problem aimed at minimizing the network cost with constraints on lifetime and connectivity. Depending on the constraints, two representative scenarios of this problem are described. We characterize the first problem, where relay nodes are not energy constrained, as a minimum set covering problem. We further consider a more challenging scenario, where all nodes are energy limited. As an optimal solution to this problem is difficult to obtain, a two-phase approach is proposed, in which locally optimal design decisions are taken. The placement of the first phase relay nodes (FPRN), which are directly connected to sensor nodes (SN), is modeled as a minimum set covering problem. To ensure the relaying of the traffic from the FPRN to the base station, three heuristic schemes are proposed to place the second phase relay nodes (SPRN). Furthermore, a lower bound on the minimum number of SPRN required for connectivity is provided. The efficiency of our proposals is investigated by numerical examples.

The authors of the above titled paper (ibid., vol. 9, no. 8, pp. 2664-2675, Aug. 2010), have become aware that several of the equations in that paper were presented with errors. In this brief, we provide correct equations. The implementation of the model in the original paper was in accordance with the correct equations, so the implementation results presented in Section V. Performance Analysis are still valid.

A simple diamond half-duplex relay network composed of a source, two decode-and-forward half-duplex relays, and a destination is considered, where a direct link between the source and the destination does not exist. For this network, we study the case of buffer-aided relays, where the relays are equipped with buffers. Each relay can receive data from the source, store it in the buffer, and forward it to the destination, when the channel conditions are advantageous. Thereby, buffering enables adaptive scheduling of the transmissions and receptions over time, which allows the network to exploit the diversity offered by the fading channels. For the considered half-duplex network, four transmission modes are defined based on whether the relay nodes receive or transmit. In this paper, we derive the locally optimal scheduling of the transmission modes over time and investigate the achievable average rate, when the relays are affected by inter-relay interference. Since the proposed buffer-aided transmission policies introduce unbounded delay, we provide a sub-optimal buffer-aided transmission policy with limited delay. Moreover, for inter-relay interference cancellation, we consider two coding schemes with different complexities. In the first scheme, we employ dirty paper coding, which entails a high complexity, whereas in the second scheme, we adopt a low-complexity technique based on successive interference cancellation at the receiving relay nodes and optimal power allocation at the transmitting nodes. Our numerical results show that the proposed protocols, with and without delay constraints, outperform existing protocols for the considered network from the literature.

The objective of this paper is to study the impact of advanced physical layer techniques on the maximum achievable throughput of wireless multihop mesh networks. We formulate a cross-layer optimization framework for the routing and scheduling problem jointly with the following physical layer techniques: successive interference cancellation, superposition coding, dirty-paper coding and their combinations. In the case when each node is enabled with superposition coding, we need to formulate a power allocation subproblem for the optimal power partition of the superimposed signals. We solve these joint problems exactly to compute the maximum achievable throughput in realistic size networks. This allows us to quantify the performance gains obtained by using these techniques (and their combinations). Specifically, we find that the use of dirty-paper coding (only at the gateway) is not justified in networks with mixed uplink and downlink flows. On the other hand, the combination of superposition coding with successive interference outperforms significantly other techniques across all transmission power range for both uplink and downlink flows. We also provide a number of interesting practical insights on throughput improvement by comparing different combinations of these techniques.

This paper deals with protocol design for cognitive cooperative systems with many secondary users. In contrast with previous cognitive configurations, the channel model considered assumes a cluster of secondary users which perform both a sensing process for transmitting opportunities and can relay data for the primary user. Appropriate relaying improves the throughput of the primary users and can increase the transmission opportunities for the cognitive users. Based on different multi-access protocols, the schemes investigated enable relaying either between the primary user and a selected secondary user or between two selected secondary users. This collaboration can be a simple distributed multiple-input single-output transmission of the primary data or a simultaneous transmission of primary and secondary data using dirty-paper coding (DPC). The parametrization of DPC as well as its combination with opportunistic relay selection yields an interesting trade-off between the primary and the secondary performance which is investigated by theoretical and simulation results under the perspective of a desired primary throughput. The proposed protocols are studied from a networking point of view and the stable throughput for primary and secondary users is derived based on the principles of queueing theory.

The sum capacity of a Gaussian broadcast MIMO channel can be achieved with dirty paper coding (DPC). However, algorithms that approach the DPC sum capacity do not appear viable in the forseeable future, which motivates lower complexity interference suppression techniques. Block diagonalization (BD) is a linear preceding technique for downlink multiuser MIMO systems. With perfect channel knowledge at the transmitter, BD can eliminate other users' interference at each receiver. In this paper, we study the sum capacity of BD with and without receive antenna selection. We analytically compare BD without receive antenna selection to DPC for a set of given channels. It is shown that (1) if the user channels are orthogonal to each other, then BD achieves the same sum capacity as DPC; (2) if the user channels lie in the same subspace, then the gain of DPC over BD can be upper bounded by the minimum of the number of transmit and receive antennas. These observations also hold for BD with receive antenna selection. Further, we study the ergodic sum capacity of BD with and without receive antenna selection in a Rayleigh fading channel. Simulations show that BD can achieve a significant part of the total throughput of DPC. An upper bound on the ergodic sum capacity gain of DPC over BD is proposed for easy estimation of the gap between the sum capacity of DPC and BD without receive antenna selection.

We consider the downlink of a wireless cellular network where the base stations are equipped with multiple antennas and operate in the same frequency band. Since scheduling changes the spatial transmit signal processing with each time slot, information from neighboring base stations is required for data encoding. This can, in theory, be accomplished by a high-capacity backhaul network through which the base stations exchange channel state information (CSI) and other control signals. In reality, however, the temporal granularity of the scheduler does not allow for timely distribution of CSI among base stations. We propose a two-phase scheduler which optimizes the precoding in the first phase and allows the users to feed back their instantaneous interference power in the second phase. For the single-user case, we present a practical scheme that combines two-phase scheduling with precoders that maximize the signal-to-leakage-plus-noise ratio. If the users feed back the interference power together with a supported rate, communication between base stations can be limited to integers. By comparing the performance to multi-user two-phase scheduling with dirty paper coding and to algorithms that share CSI among base stations we show that two-phase scheduling is a technically and practically feasible solution to deal with non-stationary intercell interference.

This paper proposes a new transmission policy for intelligent reflecting surface (IRS) empowered wireless powered internet of things systems. Particularly, an energy station (ES) wirelessly charges for multiple IoT devices during downlink wireless energy transfer (WET) and then these devices deliver their own message to an access point (AP) during uplink wireless information transfer (WIT). Also, an IRS is deployed to improve energy harvesting and data transmission capabilities. To enhance self-sustainability of the IRS, the IRS harvests energy from the ES based on the harvest-then-transmit protocol. In this paper, we maximize the sum throughput via optimizing the phase shifts of the IRS, the transfer time scheduling as well as the power splitting ratio. Due to the non-convexity of the formulated problem, we divide the problem into two sub-problems, each of which can be handled separately. Then, we adopt an alternating optimization (AO) algorithm with the semidefinite programming (SDP) relaxation. Also, we consider a special case where the circuit power consumption of IoT devices can be neglected. In this case, we derive a closed form solution for the optimal transmission time slots, power allocation and phase shift by the Lagrange dual method. Finally, numerical evaluations validate effectiveness of the proposed scheme, which significantly benefits from the IRS in improving network throughput.

This paper investigates a joint resource allocation for ultra-reliable and low-latency radio access networks (URLLRANs) with edge computing. Compared with conventional networks, URLLRANs have more restrictive latency and reliability requirements, and always feature short packet communications. It is a challenging work to provide edge computing services in URLLRANs, since the processing and transmission delay as well as packet loss during computation and communications should all be taken into considerations. Along these lines, to specify the trade-off between latency and reliability, this paper defines computation rates and transmission rates for short packets. Different from the existing work, the proposal takes effective information as well as energy consumption as performance metrics based on the definition. The packet request rates, computation latency, service rates, communication power, blocklength, and transmission information amounts are jointly optimized to reduce energy consumption and meanwhile generate more effective information for both the computation system and the communication system. To solve the NP-hard problem, the locally optimal solution and global optimal solution are both derived. Simulation results validate the performance advantage of the proposal and also indicate that the locally optimal solution can greatly reduce the computation complexity with only a small performance loss when compared with the global optimal solution.

In this paper, the problem of Quality-of-Service (QoS) differentiation is studied in the context of Buffer-Aided (BA) cooperative Free Space Optical (FSO) communication systems. This is particularly true since the existing relevant literature overlooked the possibility of preferential treatment of data packets based on their delay requirements. Inspired by this observation, this paper proposes to classify the data packets emanating from the source node into either Delay Tolerant (DT) packets or Non Delay Tolerant (NDT) ones and to service these packets according to this classification at the relay node. Priority queueing is first introduced in the relay’s buffer with a view to improving the delay experienced by NDT packets. Class of service mutation is then proposed as a starvation mitigation strategy to better manage the interesting dynamics resulting from the co-existence of packets having different QoS requirements in the same buffer. The various performance measures of interest for the explored QoS-aware communication system are both evaluated mathematically based on a Markov chain analysis and validated through extensive simulations. An asymptotic analysis is also carried out highlighting the dependence of the performance on the system parameters in an intuitive manner.

International audience; Massive machine-type communications (mMTC) is one of the main services delivered by the fifth Generation (5G) mobile network. The traditional cellular architecture where all devices connect to the base station is not energy efficient. For this reason, the use of device-to-device (D2D) communications is considered to reduce the energy consumption of mMTC devices. The main idea is to use nearby user equipment (UE) as a relay and establish with it D2D communication. However, the relay selection process also consumes energy, and this consumption can be significant compared to the energy consumed during the data transmission phase. In this paper, we propose a distributed energy-efficient D2D relaying mechanism for mMTC applications. This mechanism favors the selection of the UEs with low path loss with the mMTC device. Through mathematical analysis and simulations, we show that our mechanism allows a reduction of the total energy consumption of mMTC devices (up to 75% compared to direct transmission) when they have an unfavorable link budget. Moreover, our mechanism achieves almost constant energy consumption for a large range of UE densities and distances between the mMTC device and the base station.

Wireless caching networks have been extensively researched as a promising technique for supporting the massive data traffic of multimedia services. Many of the existing studies on real-data traffic have shown that users of a multimedia service consecutively request multiple contents and this sequence is strongly dependent on the related list of the first content and/or the top referrer in the category. This paper thus introduces the notion of “temporary preference”, characterizing the behavior of users who are highly likely to request the next content from a certain target category (i.e., related content list). Based on this observation, this paper proposes both probabilistic caching and dynamic delivery policies for categorized contents and consecutive user demands. The proposed caching scheme maximizes the minimum of the cache hit rates for all users. In the delivery phase, a dynamic helper association policy for receiving multiple contents in a row is designed to reduce the delivery latency. By comparing with the content placement optimized for one-shot requests, numerical results verify the effects of categorized contents and consecutive user demands on the proposed caching and delivery policies.

Despite the promising high-data rate features of visible light communications (VLC), they still suffer from unbalanced services due to blockages and channel fluctuation among users. This paper introduces and evaluates a new transmission scheme which adopts cooperative non-orthogonal multiple access (Co-NOMA) in hybrid VLC/radio-frequency (RF) systems, so as to improve both system sum-rate and fairness. Consider a network consisting of one VLC access point (AP) and multiple strong and weak users, where each weak user is paired with a strong user. Each weak user can be served either directly by the VLC AP, or via the strong user which converts light information received through the VLC link, and forwards the information to the weak user via the RF link. The paper then maximizes a network-wide weighted sum-rate, so as to jointly determine the strong-weak user-pairs, the serving link of each weak user (i.e., either direct VLC or hybrid VLC/RF), and the power of each user message, subject to user connectivity and transmit power constraints. The paper tackles such a mixed-integer non-convex optimization problem using an iterative approach. Simulations show that the proposed scheme significantly improves the VLC network performance (i.e., sum-rate and fairness) as compared to the conventional NOMA scheme.

In this paper, the problem of training federated learning (FL) algorithms over a realistic wireless network is studied. In particular, in the considered model, wireless users execute an FL algorithm while training their local FL models using their own data and transmitting the trained local FL models to a base station (BS) that will generate a global FL model and send it back to the users. Since all training parameters are transmitted over wireless links, the quality of the training will be affected by wireless factors such as packet errors and the availability of wireless resources. Meanwhile, due to the limited wireless bandwidth, the BS must select an appropriate subset of users to execute the FL algorithm so as to build a global FL model accurately. This joint learning, wireless resource allocation, and user selection problem is formulated as an optimization problem whose goal is to minimize an FL loss function that captures the performance of the FL algorithm. To address this problem, a closed-form expression for the expected convergence rate of the FL algorithm is first derived to quantify the impact of wireless factors on FL. Then, based on the expected convergence rate of the FL algorithm, the optimal transmit power for each user is derived, under a given user selection and uplink resource block (RB) allocation scheme. Finally, the user selection and uplink RB allocation is optimized so as to minimize the FL loss function. Simulation results show that the proposed joint federated learning and communication framework can reduce the FL loss function value by up to 10% and 16%, respectively, compared to: 1) An optimal user selection algorithm with random resource allocation and 2) a standard FL algorithm with random user selection and resource allocation., This paper has been accepted by IEEE Transactions on Wireless Communications. Our code is available at: https://github.com/mzchen0/Wireless-FL

Recently, the so-called cell-free (CF) massive multiple-input multiple-output (MIMO) architecture has been introduced, wherein a very large number of distributed access points (APs) simultaneously and jointly serve a much smaller number of mobile stations (MSs). The paper extends the CF approach to the case in which both the APs and the MSs are equipped with multiple antennas, proposing a beamfoming scheme that, relying on the zero-forcing strategy, does not require channel estimation at the MSs. We contrast the originally proposed formulation of CF massive MIMO with a user-centric (UC) approach wherein each MS is served only by a limited number of APs. Exploiting the framework of successive lower-bound maximization, the paper also proposes and analyzes power allocation strategies aimed at either sum-rate maximization or minimum-rate maximization, both for the uplink and downlink. Results show that the UC approach, which requires smaller backhaul overhead and is more scalable that the CF deployment, also achieves generally better performance than the CF approach for the vast majority of the users, especially on the uplink.

Rendezvous is a fundamental building block in distributed cognitive-radio networks (CRNs), in which pairs or groups of users must find a jointly available channel. Research on the rendezvous problem has focused so far on minimizing the time to rendezvous (to find a suitable channel) or on maximizing the rendezvous degree (percentage of channels on which rendezvous can take place). In this paper, we model the rendezvous problem in a more realistic way that acknowledges the fact that available channels may suffer from interference which varies from location to location as well as over time. In other words, channels are influenced by heterogeneous interference. In this setting, CRNs benefit from rendezvous methods that find a quiet channel, which supports high symbol rates and does not suffer much from dropped packets. In this paper, we propose three important rendezvous design disciplines to achieve bounded rendezvous time, full rendezvous degree, and to rendezvous on quiet channels that suffer little interference. We first present the Disjoint Relaxed Difference Set (DRDS) based rendezvous algorithm as a cornerstone, which ensures rendezvous on every channel (full rendezvous degree) in bounded time. When channels suffer from heterogeneous interference, we propose the Interference based DRDS (I-DRDS) algorithm which ensures rendezvous on channels with less interference, incorporating the interference normalization and interference mapping methods. We conduct extensive simulations to evaluate the proposed algorithms; compared with the state-of-the-art algorithms, the results show that I-DRDS has the best rendezvous performance on less interfered channels, with slightly larger rendezvous time.

This paper proposes a video delivery strategy for dynamic streaming services which maximizes time-average streaming quality under a playback delay constraint in wireless caching networks. The network where popular videos encoded by scalable video coding are already stored in randomly distributed caching nodes is considered under adaptive video streaming concepts, and distance-based interference management is investigated in this paper. In this network model, a streaming user makes delay-constrained decisions depending on stochastic network states: 1) caching node for video delivery, 2) video quality, and 3) the quantity of video chunks to receive. Since wireless link activation for video delivery may introduce delays, different timescales for updating caching node association, video quality adaptation, and chunk amounts are considered. After associating with a caching node for video delivery, the streaming user chooses combinations of quality and chunk amounts in the small timescale. The dynamic decision making process for video quality and chunk amounts at each slot is modeled using Markov decision process, and the caching node decision is made based on the framework of Lyapunov optimization. Our intensive simulations verify that the proposed video delivery algorithm works reliably and also can control the tradeoff between video quality and playback latency., Comment: 28 pages, 11 figures, submission to IEEE TWC

Unmanned aerial vehicle (UAV) wireless communication has recently been recognized to be inevitable and prevalent in the fifth-generation (5G) wireless networks. In this paper, we propose a secure transmission scheme for a wiretap channel, where a source communicates with a legitimate UAV in the presence of an eavesdropper. We consider the full-duplex active eavesdropper, which performs both eavesdropping and malicious jamming simultaneously. The source transmits artificial noise (AN) signals, in addition to information signals, to confuse this eavesdropper. By considering the ground-to-UAV channel model, we analyze the hybrid outage probability, which takes both the transmission outage probability and the secrecy outage probability into consideration. We further provide the asymptotic hybrid outage probability in a more compact form, where both the transmit power at the source and the jamming power at the eavesdropper become large with a fixed ratio. Through the analysis and the numerical results, we determine the optimal power allocation factor between information signals and AN signals as well as the operating height of UAV that minimize the hybrid outage probability. We also provide the most harmful antenna configuration of the eavesdropper to the UAV communications, and this paper can be a useful framework for the design of confidential UAV communication system.

Recently, wireless streaming of on-demand videos of mobile users (MUs) has become the major form of data traffic over cellular networks. As a response, caching popular videos in the storage of small base stations (SBSs) has been regarded as an efficient approach to reduce the transmission latency and alleviate the data traffic loaded over backhaul channels. This paper considers a small-cell based caching market composed of one mobile network operator (MNO) and multiple video service providers (VSPs). In this system, the MNO manages and operates its SBSs, and assigns these SBSs’ storage to different VSPs, who have caching requirements. However, videos have different popularities and MUs present different preferences to these VSPs when they request videos. In addition, the caching service brings different utilities to different VSPs as well as that providing caching service to different VSPs causes distinct costs to the MNO. Such privacy information cannot be aware of among VSPs and the MNO. Therefore, to elicit this hidden information, this paper designs a double auction-based caching mechanism, which ensures the efficient operation of the market by maximizing the social welfare, i.e., the gap between VSPs’ caching utilities and MNO’s caching costs. Moreover, this paper demonstrates the economic properties of the designed caching mechanism, which are also validated by the simulation results.

Internet-of-Things (IoT) is a promising technology to connect massive machines and devices in the future communication networks. In this paper, we study a wireless-powered IoT network (WPIN) with short packet communication (SPC), in which a hybrid access point (HAP) first transmits power to the IoT devices wirelessly, then the devices in turn transmit their short data packets achieved by finite blocklength codes to the HAP using the harvested energy. Different from the long packet communication in conventional wireless network, SPC suffers from transmission rate degradation and a significant packet error rate. Thus, conventional resource allocation in the existing literature based on Shannon capacity achieved by the infinite blocklength codes is no longer optimal. In this paper, to enhance the transmission efficiency and reliability, we first define effective-throughput and effective-amount-of-information as the performance metrics to balance the transmission rate and the packet error rate, and then jointly optimize the transmission time and packet error rate of each user to maximize the total effective-throughput or minimize the total transmission time subject to the users’ individual effective-amount-of-information requirements. To overcome the non-convexity of the formulated problems, we develop efficient algorithms to find high-quality suboptimal solutions for them. The simulation results show that the proposed algorithms can achieve similar performances as that of the optimal solution via exhaustive search, and outperform the benchmark schemes.

In this paper, we propose a method to reuse the cyclic-prefix (CP) intervals of an ongoing OFDM link, by another link, without degrading the OFDM link performance. We label the link that reuses the CP-intervals as CPLink, as they use only the CP-intervals of the ongoing link labeled, MainLink. We leverage the fact that the most commonly used OFDM receivers discard the samples in CP-intervals to design the CPLink that ensures below-noise-floor interference at every MainLink-receiver. The key contribution in this paper is the design and study of zero-knowledge CPLink, in which the CPLink-transmitter ensures below-noise-floor interference at every MainLink-receiver with no knowledge about the locations or the number of MainLink-receivers. We analytically show that the zero-knowledge CPLink capacity is positive. For LTE frame structure with 20-MHz bandwidth and 2-km cell-radius, we evaluate the CPLink for two kinds of CPLink-receivers: full-duplex base-station and a half-duplex device. Even for the cell-edge CPLink-transmitters, full-duplex zero-knowledge CPLink data rates can be up to 20 Mbps (60 Mbps) when the CP duration is ~7% (25%) of the data-symbol duration. The half-duplex CPLink rate is 5–40 Mbps when the CPLink-transmitter is within 250 m of CPLink-receiver. CPLink capacity is found to increase near-linearly with the CP duration, thus mitigating CP overhead.

The benefit of having a complementary network such as device-to-device (D2D) communications underlaying cellular systems lies in alleviating the traffic overloading burdens at base stations (BSs). This is critical in modern-day scenarios, e.g., in offloading and caching of mobile data traffic, and delivery of popular Internet contents to users. In this paper, we are chiefly interested in the establishment of D2D networks and how such a network evolves dynamically over time as D2D links are continuously formed and broken. Another important yet challenging research opportunity, i.e., the leverage of human users’ social ties for D2D communications, will also be addressed in this paper. To investigate the D2D network formation problem, we look at a game-theoretic framework where the utility function is designed to balance the physical and social domains—where we systematically extract social tie strengths from a real-world data set. To study the evolution of such D2D networks through time in a dynamic stochastic context, we propose a dynamic potential game and show that its equilibrium behaviors can be achieved through some strategy and payoff learning mechanisms. Simulation results verify our analysis. Using a content delivery application to assess the performance of our proposed scheme, it can be shown that major improvements can be obtained in terms of network delay, content accessibility, and BS load reduction.

LTE in unlicensed spectrum using licensed assisted access LTE (LTE-LAA) is a promising approach to overcome the wireless spectrum scarcity. However, to reap the benefits of LTE-LAA, a fair coexistence mechanism with other incumbent WiFi deployments is required. In this paper, a novel deep learning approach is proposed for modeling the resource allocation problem of LTE-LAA small base stations (SBSs). The proposed approach enables multiple SBSs to proactively perform dynamic channel selection, carrier aggregation, and fractional spectrum access while guaranteeing fairness with existing WiFi networks and other LTE-LAA operators. Adopting a proactive coexistence mechanism enables future delay-tolerant LTE-LAA data demands to be served within a given prediction window ahead of their actual arrival time thus avoiding the underutilization of the unlicensed spectrum during off-peak hours while maximizing the total served LTE-LAA traffic load. To this end, a noncooperative game model is formulated in which SBSs are modeled as Homo Egualis agents that aim at predicting a sequence of future actions and thus achieving long-term equal weighted fairness with WLAN and other LTE-LAA operators over a given time horizon. The proposed deep learning algorithm is then shown to reach a mixed-strategy Nash equilibrium (NE), when it converges. Simulation results using real data traces show that the proposed scheme can yield up to 28% and 11% gains over a conventional reactive approach and a proportional fair coexistence mechanism, respectively. The results also show that the proposed framework prevents WiFi performance degradation for a densely deployed LTE-LAA network., This paper has been accepted for publication at IEEE Transaction on Wireless Communications

© 2002-2012 IEEE. Considering a multi-user interference network with an eavesdropper, this paper aims at the power allocation to optimize the worst secrecy throughput among the network links or the secure energy efficiency in terms of achieved secrecy throughput per Joule under link security requirements. Three scenarios for the access of channel state information are considered: the perfect channel state information; partial channel state information with channels from the transmitters to the eavesdropper exponentially distributed; and not perfectly known channels between the transmitters and the users with exponentially distributed errors. The paper develops various path-following procedures of low complexity and rapid convergence for the optimal power allocation. Their effectiveness and viability are illustrated through numerical examples. The power allocation schemes are shown to achieve both high secrecy throughput and energy efficiency.

Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as promising techniques in the Internet of Things (IoT) era to provide massive low-power wireless devices with enhanced computation capability and sustainable energy supply. In this paper, we propose a unified MEC-WPT design by considering a wireless powered multiuser MEC system, where a multi-antenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute computation tasks. With MEC, these users can execute their respective tasks locally by themselves or offload all or part of them to the AP based on a time division multiple access (TDMA) protocol. Building on the proposed model, we develop an innovative framework to improve the MEC performance, by jointly optimizing the energy transmit beamformer at the AP, the central processing unit (CPU) frequencies and the numbers of offloaded bits at the users, as well as the time allocation among users. Under this framework, we address a practical scenario where latency-limited computation is required. In this case, we develop an optimal resource allocation scheme that minimizes the AP's total energy consumption subject to the users' individual computation latency constraints. Leveraging the state-of-the-art optimization techniques, we derive the optimal solution in a semi-closed form. Numerical results demonstrate the merits of the proposed design over alternative benchmark schemes., Accepted by IEEE Transactions on Wireless Communications and part of this paper has been presented in IEEE ICC 2017

This paper studies the secrecy performance of a wireless network (primary network) overlaid with an ambient RF energy harvesting Internet of Things (IoT) network (secondary network). The nodes in the secondary network are assumed to be solely powered by ambient RF energy harvested from the transmissions of the primary network. We assume that the secondary nodes can eavesdrop on the primary transmissions due to which the primary network uses secrecy guard zones . The primary transmitter goes silent if any secondary receiver is detected within its guard zone. Using tools from stochastic geometry, we derive the probability of successful connection of the primary network as well as the probability of secure communication. Two conditions must be jointly satisfied in order to ensure successful connection: 1) the signal-to-interference-plus-noise ratio (SINR) at the primary receiver is above a predefined threshold, and 2) the primary transmitter is not silent. In order to ensure secure communication, the SINR value at each of the secondary nodes should be less than a predefined threshold. Clearly, when more secondary nodes are deployed, more primary transmitters will remain silent for a given guard zone radius, which will in turn impact the amount of energy harvested by the secondary network. Our results concretely show the existence of an optimal deployment density for the secondary network that maximizes the density of nodes that are able to harvest sufficient amount of energy. Furthermore, we show the dependence of this optimal deployment density on the guard zone radius of the primary network. In addition, we show that the optimal guard zone radius selected by the primary network is a function of the deployment density of the secondary network. This interesting coupling between the performance of the two networks is studied using tools from game theory. We propose an algorithm that can assist the two networks to converge to Nash equilibrium. The convergence of this algorithm is verified using simulations. Overall, this paper is one of the few concrete works that symbiotically merge tools from stochastic geometry and game theory.

This paper investigates the security-delay trade-off of the buffer-aided relay selection scheme in a two-hop wireless system, which consists of a source-destination pair, one eavesdropper, and multiple relays each having a finite buffer. To evaluate the security and delay performances of the system, we derive analytical expressions for the end-to-end (E2E) secure transmission probability (STP) and the expected E2E delay under both perfect and partial eavesdropper channel state information (CSI) cases. These analytical expressions help us to explore the inherent trade-off between the security and delay performances of the concerned system. In particular, the results in this paper indicate that: 1) the maximum E2E STP increases as the constraint on the expected E2E delay becomes less strict, and such trend is more sensitive to the variation of the number of relays than that of the relay buffer size; 2) on the other hand, the minimum expected E2E delay tends to decrease when a less strict constraint on E2E STP is imposed, and this trend is more sensitive to the variation of the relay buffer size than that of the number of relays.

A cross-layer based asymmetric resource allocation strategy for multi-destination relay systems in cellular downlink is proposed in this paper. Existing cross-layer schemes on relay networks are based on symmetric resource allocation (RA) where the transmit duration is assumed to be symmetric between base station to relay station (RS) and RS to mobile station links. This may not be realistic and hence our proposed model considers an asymmetric RA (ARA) in which the transmit durations are asymmetric. Very little work has been done in asymmetric resource allocation and many have failed to consider the queue stability and quality of service (QoS) requirements. Packet length ratio is also ignored in many of these works. In this paper, maximum delay threshold, minimum data rate requirement and zero overflow are considered as QoS requirements. This paper evolves an optimal cross-layer based ARA taking into account the above-mentioned factors. Simulation results are also verified in a cellular testbed which shows that the proposed ARA serves the edge users satisfactorily. Cellular parameters, such as blocking ratio, operating expenditure, electromagnetic pollution index, and QoS assurance, are evaluated and compared.

This paper considers the problem of achieving global channel knowledge throughout a fully connected packetized wireless network with time-varying channels. While the value of channel state information at the transmitter (CSIT) is now well known, there are many scenarios in which it is helpful to have additional channel knowledge beyond conventional CSIT, e.g., cooperative communication systems. The overhead required for global CSI knowledge can be significant, particularly in time-varying channels where the quality of channel estimates is dominated by the “staleness” of the CSI. Nevertheless, the fundamental limits and feasibility of tracking global CSI throughout a network have not been sufficiently studied. This paper presents a framework for analyzing the staleness of protocols that estimate and disseminate CSI to all nodes in a fully connected network. Fundamental bounds on achievable staleness are derived, and efficient dissemination protocols are developed, which achieve these limits. The results provide engineering guidelines on the feasibility of tracking global CSI as a function of network size, the size and composition of the packets, packet error rate, and channel coherence time.

In face of the explosive service demands, solving the problem of spectrum scarcity is becoming more important than ever. To utilize the spectrum resources more thoroughly and efficiently, virtualization technologies have been proposed, which can be a means to mitigating resource granularity and increasing efficiency in heterogeneous network environments. In this paper, a traffic-oriented resource virtualization with demand-supply dynamic analysis is proposed for optimized resource allocation of heterogeneous networks with multiple types of services. On the supply side, i.e., the network side, a low-complexity matching game approach is introduced with the novel “Match-Degree” conception, which could be defined with the Grey relational analysis. The complexity of generating preference list can be reduced by unifying various dimensions of network parameters. On the demand side, i.e., the user side, bandwidth allocation algorithm is designed to consider the comprehensive network traffic characteristics, energy consumption, and network price factors, to maximize the overall utility. Except from theoretic analysis, simulation has also been employed to compare the proposed scheme with prior and traditional ones. To further verify the practicability, tractability, and effectiveness of the proposed demand-supply scheme, a test bed is designed and developed in this paper.

In this paper, we study the capacity of wireless networks with directed energy (DE) links in the presence of obstacles. DE links are highly focused wireless links that can be treated as “pencil beam,” an example of which is the E-band link (71–76 and 81–86 GHz) newly made available by the FCC. The 10-GHz spectrum of E-band is 50-times that of the entire cellular spectrum and provides the much needed spectrum in today’s world of exponential growth in mobile applications. Since the performance of highly focused DE links are highly susceptible to the presence of obstacles and real-world applications typically involve obstacles, it is important to study the capacity of wireless networks with DE links in the presence of obstacles, which is the subject of this paper. In the following, we first provide a study of probability distribution of DE links in the presence of obstacles and investigate how the number, shape, and size of obstacles impact the DE link probability distribution. Then, based on the probability distribution of DE links, we derive the capacity scaling laws for wireless networks in the presence of obstacles. Furthermore, our results can be extended to obstacles with arbitrary shapes quite accurately.

Channel sharing in TV whitespace (TVWS) is challenging because of signal propagation characteristics and diversity in network technologies employed by secondary networks coexisting in TVWS. In this paper, the TVWS sharing problem is modeled as a multiobjective optimization problem, where each objective function tackles an important coexisting requirement, such as interference and disparity in network technologies. We propose an evolutionary algorithm that shares the TVWS among coexisting networks taking care of their channel occupancy requirements. In this paper, the channel occupancy is defined as the time duration; a network desires to radiate on a channel to achieve its desired duty cycle. Simulation results show that the proposed algorithm outperforms existing TVWS sharing algorithms regarding allocation fairness and a fraction of channel occupancy requirements of the coexisting networks.

This paper studies physical layer security in a wireless ad hoc network with numerous legitimate transmitter-receiver pairs and eavesdroppers. A hybrid full-/half-duplex receiver deployment strategy is proposed to secure legitimate transmissions, by letting a fraction of legitimate receivers work in the full-duplex (FD) mode sending jamming signals to confuse eavesdroppers upon their information receptions, and letting the other receivers work in the half-duplex mode just receiving their desired signals. The objective of this paper is to choose properly the fraction of FD receivers for achieving the optimal network security performance. Both accurate expressions and tractable approximations for the connection outage probability and the secrecy outage probability of an arbitrary legitimate link are derived, based on which the area secure link number, network-wide secrecy throughput and network-wide secrecy energy efficiency are optimized respectively. Various insights into the optimal fraction are further developed and its closed-form expressions are also derived under perfect self-interference cancellation or in a dense network. It is concluded that the fraction of FD receivers triggers a non-trivial trade-off between reliability and secrecy, and the proposed strategy can significantly enhance the network security performance., Comment: Journal paper, double-column 12 pages, 9 figures, accepted by IEEE Transactions on Wireless Communications, 2017

This paper considers a heterogeneous network architecture wherein devices use two wireless interfaces to receive packets from the base station and to transmit or receive packets from other devices concurrently. For such a network architecture, this paper focuses on time-critical and order-constrained applications that require quick and reliable in-order decoding of the packets. This paper first introduces the dual delivery delay as a measure of degradation compared with the optimal in-order packet delivery to the devices. It then addresses the minimum delivery delay problem using instantly decodable network coding (IDNC). In particular, the dual interface IDNC graph is constructed to represent all feasible coding opportunities and conflict-free transmissions. Subsequently, the minimum delivery delay problem is shown to be equivalent to a maximum weight independent set selection problem over the dual interface IDNC graph. Simulation results demonstrate that the proposed IDNC algorithm effectively reduces the delivery delay as compared with the existing network coding algorithms. Especially, for a layered video transmission, the proposed solution provides a sequential delivering of video layers to individual devices.

While stochastic geometric models based on Poisson point processes (PPPs) provide a tractable approach for the analysis of uniform two-tier network deployments, the performance evaluation of a non-uniform deployment remains an open issue, which we address in this paper. This is due to the fact that smaller cells can be more efficiently deployed in areas where the QoS of traditional macro base stations is poor. Therefore, in this paper, we introduce Stienen’s model, which allows us to analyse such non-uniform deployment. In contrast to traditional PPP-based analysis, performance characterization under the Stienen model is more challenging due to location and density dependencies. However, we demonstrate that the performance can be approximated in a tractable manner. The developed statistical framework is employed to characterize the gains in terms of energy efficiency (EE) for non-uniform deployments. Results show an achievable 19% to 124% improvement in the macrocell coverage as compared to a uniform deployment, while the femtocell coverage and system EE are of the same order of magnitude for both deployments. These results are complemented with the fact that OPEX and CAPEX are reduced due to a lesser number of FAPs deployed.

To enhance the national security, there is a growing need for government agencies to legitimately monitor suspicious communication links for preventing intended crimes and terror attacks. In this paper, we propose a new wireless information surveillance paradigm by investigating a scenario where a legitimate monitor aims to intercept a suspicious wireless communication link over fading channels. The legitimate monitor can successfully eavesdrop (decode) the information of the suspicious link at each fading state only when its achievable data rate is no smaller than that at the suspicious receiver. In practice, such legitimate eavesdropping is particularly challenging, since the legitimate monitor may be far away from the suspicious transmitter and cannot eavesdrop efficiently. To overcome this issue, we propose a new approach, namely proactive eavesdropping via cognitive jamming, in which the legitimate monitor purposely jams the receiver so as to change the suspicious communication (e.g., to a smaller data rate) for overhearing more efficiently. In particular, we consider delay-sensitive and delay-tolerant applications for the suspicious data communications, under which the legitimate monitor maximizes the eavesdropping non-outage probability for event-based monitoring and the relative eavesdropping rate for content analysis, respectively, by optimizing its jamming power allocation over different fading states subject to an average power constraint. Numerical results show that the proposed proactive eavesdropping via cognitive jamming approach greatly outperforms the conventional passive eavesdropping without jamming and the proactive eavesdropping with constant-power jamming., This paper has been accepted to appear in IEEE Transactions on Wireless Communications

Light Fidelity (LiFi) is a recently proposed technology that uses 300 THz visible light spectrum for high speed wireless communications as well as providing illumination. Basically, a LiFi access point (AP) covers only a few square meters, enabling a dense deployment of LiFi APs to improve the network throughput. However, channel blockage and shadowing in conjunction with inter-cell interference compromise the connectivity and system throughput of LiFi networks. In this paper, a network structure that combines LiFi with the conventional radio frequency (RF) system is considered. Users experiencing strong blockages can be switched to the RF system to achieve a higher data rate. In this paper, blockages, random orientation of LiFi receivers, and the user data rate requirement are characterised to model a practical communication scenario. A novel load balancing (LB) scheme based on evolutionary game theory is proposed for hybrid LiFi/RF networks. The performance of the proposed scheme is comprehensively analyzed. Results show that compared to state-of-the-art LB algorithms, the proposed scheme greatly improves user satisfaction levels at reduced computational complexity. Also, an optimal orientation of LiFi receivers and blockage density in hybrid networks would maximize the users quality of service.

Wireless network deployments in industry often grow organically with new technologies added over time, among which many use the non-licensed spectrum to avoid licensing costs. As a result, technologies competing for the same spectrum end up deployed in the same area, causing coexistence problems to manifest themselves at a later stage. To avoid unexpected performance degradation, there is a need to evaluate the impact of additional wireless technologies on an existing network before the actual deployment. This paper proposes to simplify the impact assessment by emulating the signals of the potential wireless network with a single software-defined radio. To evaluate the emulator’s performance, the impact of Bluetooth on Wi-Fi technology is considered as the reference scenario. A series of real-life experiments with configurable traffic load and network scale are conducted to estimate the impact of Bluetooth network on a Wi-Fi link, and the corresponding measurements are repeated with the emulated Bluetooth signals. To the best of the authors’ knowledge, we are the first to propose such a solution, and it is shown that the use of our emulator gives a reliable indication of the expected impact at the location of the Wi-Fi link. As such, this paper provides an important step toward a simple, cost efficient, and reliable solution, to assess the impact of a wireless network prior to its deployment.

This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications and abstract the model as equally slotted time for all users, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The consideration of asymmetric rates for receivers reflects more practical application scenarios and introduces a new trade-off between the choice of coding combinations for various receivers and the broadcasting rate for achieving shorter completion time. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. The highest weight clique in the created graph being potentially not unique, the paper further suggests a multi-layer version of the proposed solution to improve the obtained results from the employed completion time approximation. Simulation results indicate that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme.

We propose a robust resource allocation framework to improve the physical layer security in the presence of an active eavesdropper. In the considered system, we assume that both legitimate receiver and eavesdropper are full-duplex (FD) while most works in the literature concentrate on passive eavesdroppers and half-duplex (HD) legitimate receivers. In this paper, the adversary intends to optimize its transmit and jamming signal parameters so as to minimize the secrecy data rate of the legitimate transmission. In the literature, assuming that the receiver operates in HD mode, secrecy data rate maximization problems subject to the power transmission constraint have been considered in which cooperating nodes act as jammers to confound the eavesdropper. This paper investigates an alternative solution in which we take advantage of FD capability of the receiver to send jamming signals against the eavesdroppers. The proposed self-protection scheme eliminates the need for external helpers. Moreover, we consider the channel state information uncertainty on the links between the active eavesdropper and other legitimate nodes of the network. Optimal power allocation is then obtained based on the worst-case secrecy data rate maximization, under a legitimate transmitter power constraint in the presence of the active eavesdropper. Numerical results confirm the advantage of the proposed secrecy design and in certain conditions, demonstrate substantial performance gain over the conventional approaches.

In this paper, we study the benefits of full-duplex (FD) receiver jamming in enhancing the physical-layer security of a two-tier decentralized wireless network with each tier deployed with a large number of pairs of a single-antenna transmitter and a multi-antenna receiver. In the underlying tier, the transmitter sends unclassified information, and the receiver works in the halfduplex (HD) mode receiving the desired signal. In the overlaid tier, the transmitter deliveries confidential information in the presence of randomly located eavesdroppers, and the receiver works in the FD mode radiating jamming signals to confuse eavesdroppers and receiving the desired signal simultaneously. We provide a comprehensive performance analysis and network design under a stochastic geometry framework. Specifically, we consider the scenarios where each FD receiver uses single- and multi-antenna jamming, and analyze the connection probability and the secrecy outage probability of a typical FD receiver by providing accurate expressions and more tractable approximations for the two metrics. We further determine the optimal deployment of the FD-mode tier in order to maximize networkwide secrecy throughput subject to constraints including the given dual probabilities and the network-wide throughput of the HD-mode tier. Numerical results are demonstrated to verify our theoretical findings, and show that network-wide secrecy throughput is significantly improved by properly deploying the FD-mode tier., Comment: Journal paper, double column, 15 pages, 11 figures, accepted to appear on IEEE Transactions on Wireless Communications

Cloud radio networks coordinate transmission among base stations (BSs) to reduce the interference effects, particularly for the cell-edge users. In this paper, we analyze the performance of a cloud network with static clustering where geographically close BSs form a cloud network of cooperating BSs. Due to finite cooperation, the interference in a practical cloud radio cannot be removed, and in this paper, the distance-based interference is taken into account in the analysis. In particular, we consider centralized zero forcing equalizer and dirty paper precoding for canceling the interference. Bounds are developed on the signal-to-interference ratio distribution and achievable rate with full and limited channel feedback from the cluster users. The adverse effect of finite clusters on the achievable rate is quantified. We show that the number of cooperating BSs is more crucial than the cluster area when full channel state information from the cluster is available for precoding. Also, we study the impact of limiting the channel state information on the achievable rate. We show that even with a practically feasible feedback of about five to six channel states from each user, significant gain in mean rate and cell edge rate compared with conventional cellular systems can be obtained.

3GPP introduced the key management mechanism (KMM) in evolved multimedia broadcast/multicast service (eMBMS) to provide forward security and backward security for multicast contents. In this paper, we point out that KMM may lead to frequent rekeying and re-authentication issues due to eMBMS's characteristics: 1) massive group members; 2) dynamic group topology; and 3) unexpected wireless disconnections. Such issues expose extra load for both user equipment (UE) terminals and mobile operators. It seems prolonging the rekeying interval is an intuitive solution to minimizing the impact of the issues. However, a long rekeying interval is not considered the best operational solution due to revenue loss of content providers. This paper quantifies the tradeoff between the load of the UEs and the operators as well as the revenue loss of the content providers. Moreover, we emphasize how essential this rekeying interval has impacts on the problems. Using our proposed tradeoff model, the operators can specify a suitable rekeying interval to best balance the interest between the above three parties. The tradeoff model is validated by extensive simulations and is demonstrated to be an effective approach for the tradeoff analysis and optimization on eMBMS.

Rendezvous is the fundamental challenge in cognitive radio networks to find each other on a specific channel and establish a communication link. The primary focus of this paper is to design an algorithm for blind rendezvous, i.e., a rendezvous without a coordinator or common control channel. Channels to jump are assumed to be homogeneous in prior work; however, in the real world, channels exhibit different conditions. Therefore, we propose an adaptive jumping pattern such that a superior channel is considered more frequently based on its noise level and users have a greater possibility to rendezvous on such a channel. Furthermore, in this paper, we investigate the rendezvous problem with multiple radio interfaces. When multiple radio interfaces are available for users, the possibility of rendezvous increases; however, the number of channels to jump for each interface may not be the same as other users’ interfaces. We propose an adaptive rendezvous algorithm that can function for multiple interfaces and different sizes of channel lists and an adaptive jumping pattern for different channel conditions. We prove that the proposed algorithm provides guaranteed rendezvous and derive the maximum time-to-rendezvous (TTR), which is also verified via simulation results. Further, our algorithm outperforms jump-and-stay in terms of TTR while enabling users to rendezvous on a better channel.

As the growth of mobile data traffic places significant strain on cellular networks, plans for exploiting under-utilized network resources become increasingly attractive. In this paper, we propose, design, and evaluate a data offloading architecture, where mobile users are offloaded to mesh networks, which are built and managed by residential users. Such networks are often developed in the context of community networks or, recently, as commercial services. Mobile network operators can lease capacity from these networks and offload traffic to reduce their servicing costs. We introduce an analytical framework that determines the offloading policy, i.e., which mobile users should be offloaded, based on the energy cost induced to the cellular base stations. Accordingly, we design a minimum-cost servicing policy for the mesh networks. Clearly, such architectures are realizable only if the mesh nodes agree with each other to jointly serve the offloaded traffic. To achieve this, we employ the Shapley value rule for dispensing the leasing payment among the mesh nodes. We evaluate this paper by simulating the operation of the LTE-A network, and conducting test bed experiments for the mesh network. The results reveal significant savings for eNBs power consumption and reimbursements for mesh users.

A retry limit is usually adopted in practical carrier sense multiple access (CSMA) networks, where a packet is discarded if the maximum number of retransmission attempts is reached. Despite extensive studies, the effect of retry limit on the performance optimization of CSMA networks has remained largely unknown. This paper focuses on a CSMA network with a finite retry limit $M$ , and aims to address the following open issues. First, for a given retry limit $M$ , how should the backoff parameters be adaptively tuned to achieve the optimal network performance? Second, how does the optimal network performance vary with $M$ ? Specifically, in this paper, the explicit expressions of the network steady-state points, the network throughput, and moments of access delay of successfully transmitted packets are all obtained as the functions of the retry limit $M$ , based on which the optimal network performance is further characterized. It is revealed that a CSMA network with a finite retry limit $M$ may have three steady-state points, and the retry limit $M$ has distinct effects on the throughput and delay performance at these steady-state points. The maximum network throughput is found to be independent of $M$ . Yet to achieve the maximum network throughput, the aggregate input rate and the initial transmission probability of each node should be set according to $M$ in unsaturated and saturated conditions, respectively. To optimize the mean access delay, on the other hand, the initial transmission probability should be carefully selected in saturated conditions. The minimum mean access delay can be greatly reduced by choosing a smaller retry limit $M$ , which, nevertheless, leads to a significant throughput loss. The analysis sheds important light on performance optimization of practical CSMA-based networks such as IEEE 802.11 networks.

This paper considers the problem of jointly constructing and scheduling forwarding trees in a wireless sensor network, each to collect measurements from a group of sensor nodes at a single sink node. The goal is to construct such trees that gather measurements in the most energy efficient manner and with minimal gathering latency. We assume transmissions (carrying measurements) on wireless links interfere with one another, and thus, appropriate link scheduling is required to manage interference. We refer to this problem as forwarding tree construction and scheduling (FTCS). Each tree may be constructed independently, and then, its links are scheduled. However, when all trees are combined together, the shortest and energy efficient schedule may not be guaranteed. Furthermore, a large number of possible forwarding trees for each group of sensors may be considered. Both problems of enumerating forwarding trees and scheduling links for those trees are hard combinatorial problems. This is compounded by the fact that the two problems must be solved jointly, to guarantee the selection of the best forwarding trees that, when their links are scheduled, guarantee a shortest energy efficient schedule. After highlighting the complexity of the FTCS problem, we present a novel primal-dual decomposition method using column generation. We also highlight several challenges we faced when solving the decomposed problem and present efficient techniques for mitigating those challenges. One major advantage of this paper is that it can serve as a benchmark for evaluating the performance of any low complexity method for solving the FTCS problem for larger network instances, where no known exact solutions can be found.

Recent pioneer work has shown that packet receptions on adjacent links are correlated, which contradicts the long held assumption that wireless links are statistically independent. Since wireless link correlation affects a wide range of protocol designs, it is essential to quantify the impact generically. In particular, this paper focuses on a unified transmission cost metric for diversity-based routing schemes, including opportunistic routing, network coding, and hybrid routing. This paper covers both unicast and broadcast. Compared with the legacy metrics, our metric provides a direct and accurate estimation of the transmission cost in the presence of link correlation. The new metric helps a wide range of routing algorithms determine when they can benefit from reception diversity, and how to maximize the benefit, at negligible costs. We evaluate the metric on one 802.11 test bed and three 802.15.4 test beds running TelosB, MICAz, and GreenOrbs nodes. The experimental results show that our metric 1) reduces 92% and 94% of the estimation error of the transmission cost in unicast and broadcast and 2) outperforms the link independent metric in both unicast and broadcast applications.

The densification and expansion of wireless network pose new challenges on interference management and reducing energy consumption. This paper studies energy-efficient resource management in heterogeneous networks by jointly optimizing cell activation, user association and multicell multiuser channel assignment, according to the long-term average traffic and channel conditions. The proposed framework is built on characterizing the interference coupling by pre-defined interference patterns, and performing resource allocation among these patterns. In this way, the interference fluctuation caused by (de)activating cells is explicitly taken into account when calculating the user achievable rates. A tailored algorithm is developed to solve the formulated problem in the dual domain by exploiting the problem structure, which gives a significant complexity saving. Numerical results show a huge improvement in energy saving achieved by the proposed scheme. The user association derived from the proposed joint resource optimization is mapped to standard-compliant cell selection biasing. This mapping reveals that the cell-specific biasing for energy saving is quite different from that for load balancing investigated in the literature., This is an extended version of a paper to appear in IEEE Transactions on Wireless Communications with the same title, containing all detailed proofs