Multi-packet reception (MPR) has been recognized as a powerful capacity-enhancement technique for randomaccess wireless local area networks (WLANs). As is common with all random access protocols, the wireless channel is often under-utilized in MPR WLANs. In this paper, we propose a novel multi-round contention random-access protocol to address this problem. This work complements the existing randomaccess methods that are based on single-round contention. In the proposed scheme, stations are given multiple chances to contend for the channel until there are a sufficient number of ?winning? stations that can share the MPR channel for data packet transmission. The key issue here is the identification of the optimal time to stop the contention process and start data transmission. The solution corresponds to finding a desired tradeoff between channel utilization and contention overhead. In this paper, we conduct a rigorous analysis to characterize the optimal strategy using the theory of optimal stopping. An interesting result is that the optimal stopping strategy is a simple threshold-based rule, which stops the contention process as soon as the total number of winning stations exceeds a certain threshold. Compared with the conventional single-round contention protocol, the multi-round contention scheme significantly enhances channel utilization when the MPR capability of the channel is small to medium. Meanwhile, the scheme automatically falls back to single-round contention when the MPR capability is very large, in which case the throughput penalty due to random access is already small even with single-round contention.
In related work, @cite_0 attempts to enhance the utilization of MPR channels by allowing stations to count down and transmit as long as there are less than @math ongoing transmissions in the air. To do this, one key assumption is that a station is able to detect the number of ongoing transmissions using an energy detector. This assumption, however, is not valid in wireless networks, where the received energy from each transmitting station is random and unknown a priori.
@cite_0
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Motivated by the ongoing discussion on coordinated multipoint in wireless cellular standard bodies, this paper considers the problem of base station cooperation in the downlink of heterogeneous cellular networks. The focus of this paper is the joint transmission scenario, where an ideal backhaul network allows a set of randomly located base stations, possibly belonging to different network tiers, to jointly transmit data, to mitigate intercell interference and hence improve coverage and spectral efficiency. Using tools from stochastic geometry, an integral expression for the network coverage probability is derived in the scenario where the typical user located at an arbitrary location, i.e., the general user, receives data from a pool of base stations that are selected based on their average received power levels. An expression for the coverage probability is also derived for the typical user located at the point equidistant from three base stations, which we refer to as the worst case user. In the special case where cooperation is limited to two base stations, numerical evaluations illustrate absolute gains in coverage probability of up to 17 for the general user and 24 for the worst case user compared with the noncooperative case. It is also shown that no diversity gain is achieved using noncoherent joint transmission, whereas full diversity gain can be achieved at the receiver if the transmitting base stations have channel state information. Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated. Due to its simplicity and cost efficiency, wireless local area network (WLAN) enjoys unique advantages in providing high-speed and low-cost wireless services in hot spots and indoor environments. Traditional WLAN medium-access-control (MAC) protocols assume that only one station can transmit at a time: simultaneous transmissions of more than one station cause the destruction of all packets involved. By exploiting recent advances in PHY-layer multiuser detection (MUD) techniques, it is possible for a receiver to receive multiple packets simultaneously. This paper argues that such multipacket reception (MPR) capability can greatly enhance the capacity of future WLANs. In addition, the paper provides the MAC-layer and PHY-layer designs needed to achieve the improved capacity. First, to demonstrate MPR as a powerful capacity-enhancement technique, we prove a "superlinearityrdquo result, which states that the system throughput per unit cost increases as the MPR capability increases. Second, we show that the commonly deployed binary exponential backoff (BEB) algorithm in today's WLAN MAC may not be optimal in an MPR system, and the optimal backoff factor increases with the MPR capability, the number of packets that can be received simultaneously. Third, based on the above insights, we design a joint MAC-PHY layer protocol for an IEEE 802.11-like WLAN that incorporates advanced PHY-layer signal processing techniques to implement MPR. We investigate the optimal selection of minimum contention window values to achieve proportional fairness in a multirate IEEE 802.11e test-bed. Unlike other approaches, the proposed model accounts for the contention-based nature of 802.11's MAC layer operation and considers the case where stations can have different weights corresponding to different throughput classes. Our test-bed evaluation considers both the long-term throughput achieved by wireless stations and the short-term fairness. When all stations have the same transmission rate, optimality is achieved when a station's throughput is proportional to its weight factor, and the optimal minimum contention windows also maximize the aggregate throughput. When stations have different transmission rates, the optimal minimum contention window for high rate stations is smaller than for low rate stations. Furthermore, we compare proportional fairness with time-based fairness, which can be achieved by adjusting packet sizes so that low and high rate stations have equal successful transmission times, or by adjusting the transmission opportunity (TXOP)limit so that high rate stations transmit multiple back-to-back packets and thus occupy the channel for the same time as low rate stations that transmit a single packet. The test-bed experiments show that when stations have different transmission rates and the same weight, proportional fairness achieves higher performance than the time-based fairness approaches, in terms of both aggregate utility and throughput. The acute disparity between increasing bandwidth demand and available spectrum has brought millimeter wave (mmWave) bands to the forefront of candidate solutions for the next-generation cellular networks. Highly directional transmissions are essential for cellular communication in these frequencies to compensate for higher isotropic path loss. This reliance on directional beamforming, however, complicates initial cell search since mobiles and base stations must jointly search over a potentially large angular directional space to locate a suitable path to initiate communication. To address this problem, this paper proposes a directional cell discovery procedure where base stations periodically transmit synchronization signals, potentially in time-varying random directions, to scan the angular space. Detectors for these signals are derived based on a Generalized Likelihood Ratio Test (GLRT) under various signal and receiver assumptions. The detectors are then simulated under realistic design parameters and channels based on actual experimental measurements at 28 GHz in New York City. The study reveals two key findings: 1) digital beamforming can significantly outperform analog beamforming even when digital beamforming uses very low quantization to compensate for the additional power requirements and 2) omnidirectional transmissions of the synchronization signals from the base station generally outperform random directional scanning. Ambient radio frequency (RF) energy harvesting technique has recently been proposed as a potential solution for providing proactive energy replenishment for wireless devices. This paper aims to analyze the performance of a battery-free wireless sensor powered by ambient RF energy harvesting using a stochastic geometry approach. Specifically, we consider the point-to-point uplink transmission of a wireless sensor in a stochastic geometry network, where ambient RF sources, such as mobile transmit devices, access points and base stations, are distributed as a Ginibre @math -determinantal point process (DPP). The DPP is able to capture repulsion among points, and hence, it is more general than the Poisson point process (PPP). We analyze two common receiver architectures: separated receiver and time-switching architectures. For each architecture, we consider the scenarios with and without co-channel interference for information transmission. We derive the expectation of the RF energy harvesting rate in closed form and also compute its variance. Moreover, we perform a worst-case study which derives the upper bound of both power and transmission outage probabilities. Additionally, we provide guidelines on the setting of optimal time-switching coefficient in the case of the time-switching architecture. Numerical results verify the correctness of the analysis and show various tradeoffs between parameter setting. Lastly, we prove that the RF-powered sensor performs better when the distribution of the ambient sources exhibits stronger repulsion. Block diagonalization (BD) is a precoding technique that eliminates interuser interference in downlink multiuser multiple-input multiple-output (MIMO) systems. With the assumptions that all users have the same number of receive antennas and utilize all receive antennas when scheduled for transmission, the number of simultaneously supportable users with BD is limited by the ratio of the number of base station transmit antennas to the number of user receive antennas. In a downlink MIMO system with a large number of users, the base station may select a subset of users to serve in order to maximize the total throughput. The brute-force search for the optimal user set, however, is computationally prohibitive. We propose two low-complexity suboptimal user selection algorithms for multiuser MIMO systems with BD. Both algorithms aim to select a subset of users such that the total throughput is nearly maximized. The first user selection algorithm greedily maximizes the total throughput, whereas the criterion of the second algorithm is based on the channel energy. We show that both algorithms have linear complexity in the total number of users and achieve around 95 of the total throughput of the complete search method in simulations A problem related to the decentralized control of a multiple access channel is considered: Suppose k stations from an ensemble of n simultaneously transmit to a multiple access channel that provides the feedback 0, 1, or 2+, denoting k = 0, k = 1, or k ≥ 2, respectively. If k = 1, then the transmission succeeds. But if k ≥ 2, as a result of the conflict, none of the transmissions succeed. An algorithm to resolve a conflict determines how to schedule retransmissions so that each of the conflicting stations eventually transmits singly to the channel. In this paper, a general model of deterministic algorithms to resolve conflicts is introduced, and it is established that, for all k and n (2 ≤ k ≤ n ), O( k (log n ) (log k )) time must elapse in the worst case before all k transmissions succeed. Since underwater acoustic (UWA) networks have the nature of long propagation delay, low bit rates and error-prone acoustic communication, protocols designed for underwater acoustic networks are significantly different from that of terrestrial radio networks. Limited by these nature of UWA channels, conventional medium access control (MAC) protocols of radio packet network ether have low efficiency or are not able to apply to underwater acoustic networks. It is necessary to develop an efficient MAC protocol for underwater acoustic networks. In this paper, a collision-free MAC protocol for UWA networks called Ordered Carrier Sense Multiple Access (Ordered CSMA) is proposed and analyzed. Ordered CSMA combines the concepts of round-robin scheduling and CSMA. In Ordered CSMA, each station transmits data frame in a fixed order. More specifically, each station transmits immediately after the data frame transmission of last station in the order, instead of waiting for a period of maximum propagation delay. To achieve this, each station is constantly sensing the carrier and listens to all received frames. Due to the characteristics of collision free and high channel utilization, Ordered CSMA shows a great MAC efficiency improvement in our simulations, compared to previous works. Distributed opportunistic scheduling (DOS) is inherently more difficult than conventional opportunistic scheduling due to the absence of a central entity that knows the channel state of all stations. With DOS, stations use random access to contend for the channel and, upon winning a contention, they measure the channel conditions. After measuring the channel conditions, a station only transmits if the channel quality is good; otherwise, it gives up the transmission opportunity. The distributed nature of DOS makes it vulnerable to selfish users: By deviating from the protocol and using more transmission opportunities, a selfish user can gain a greater share of wireless resources at the expense of "well-behaved" users. In this paper, we address the problem of selfishness in DOS from a game-theoretic standpoint. We propose an algorithm that satisfies the following properties: 1) When all stations implement the algorithm, the wireless network is driven to the optimal point of operation; and 2) one or more selfish stations cannot obtain any gain by deviating from the algorithm. The key idea of the algorithm is to react to a selfish station by using a more aggressive configuration that (indirectly) punishes this station. We build on multivariable control theory to design a mechanism for punishment that is sufficiently severe to prevent selfish behavior, yet not so severe as to render the system unstable. We conduct a game-theoretic analysis based on repeated games to show the algorithm's effectiveness against selfish stations. These results are confirmed by extensive simulations. Having the channel state information of the channels over which the signals propagate from the transmitter to the receiver available at both sides of the transmission link is beneficial in many wireless applications. However, in frequency division duplex systems, a base station can only estimate the channel transfer function of the uplink channel based on the transmission of a-priori known training signals from the mobile station. A mobile station can only estimate the channel transfer function of the downlink channel based on the transmission of a-priori known training signals from the base station. Due to the frequency selective behavior of the mobile radio channel, the channel transfer functions of the uplink channel are different from the channel transfer functions of the downlink channel. In order to obtain the channel state information of the downlink channel in the base station or the channel state information of the uplink channel in the mobile station it is possible to feed back this information from the mobile station to the base station or from the base station to the mobile station. However, this feedback of the channel state information decreases the spectral efficiency. This paper introduces novel techniques to obtain the channel state information of the downlink channel in the base station based on the channel state information of the uplink channel in multiple antenna systems. Measurement results show the good performance of the investigated techniques. Thus, the signalling overhead can be reduced. Decentralized camera sensors capture a 3D scene of interest from multiple perspectives. The captured video signals need to be transmitted to a central station over a shared wireless channel. A collocated server streams the gathered data to a collection of clients interested in experiencing the scene interactively. We design a constrained optimization framework for sharing the transmission bandwidth of the wireless channel across the sensors such that the average video quality over the client population is maximized. We consider scheduling the uplink resources of the wireless channel at the view or packet level. In the first case, the central station partitions the channel capacity across a select subset of views that are transmitted entirely. In the second case, the station coordinates the packet transmissions of every sensor. We formulate exact and approximate algorithms to solve the optimization of interest. We examine their transmission efficiency via simulation experiments that demonstrate considerable gains over the state-of-the-art and study the impact of view popularity. In a wireless multimedia sensor network (WMSN), the minimization of network energy consumption is a crucial task not just for scalar data but also for multimedia. In this network, a camera node (CN) captures images and transmits them to a base station (BS). Several sensor nodes (SNs) are also placed throughout the network to facilitate the proper functioning of the network. Transmitting an image requires a large amount of energy due to the image size and distance; however, SNs are resource constrained. Image compression is used to scale down image size; however, it is accompanied by a computational complexity trade-off. Moreover, direct image transmission to a BS requires more energy. Thus, in this paper, we present a distributed image compression architecture over WMSN for prolonging the overall network lifetime (at high throughput). Our scheme consists of three subtasks: determining the optimal camera radius for prolonging the CN lifetime, distributing image compression tasks among the potential SNs to balance the energy, and, finally, adopting a multihop hierarchical routing scheme to reduce the long-distance transmission energy. Simulation results show that our scheme can prolong the overall network lifetime and achieve high throughput, in comparison with a traditional routing scheme and its state-of-the-art variants. In a Wireless Sensor Network (WSN) the sensed data must be gathered and transmitted to a base station where it is further processed by end users. Since that kind of network consists of low-power nodes with limited battery power, power efficient methods must be applied for node communication and data gathering in order to achieve long network lifetimes. In such networks where in a round of communication many sensor nodes have data to send to a base station, it is very important to minimize the total energy consumed by the system so that the total network lifetime is maximized. The lifetime of such sensor network is the time until base station can receive data from all sensors in the network. In this work1, besides the conventional protocol of direct transmission or the use of dynamic routing protocols proposed in literature that potentially aggregates data, we propose an algorithm based on static routing among sensor nodes with unequal energy distribution in order to extend network lifetime and find a near-optimal node energy charge scheme that leads to both node and network lifetime prolongation. Our simulation results show that our algorithm achieves longer network lifetimes mainly because the final energy charge of each node is not uniform, while each node is free from maintaining complex route information and thus less infrastructure communication is needed. This paper studies a multi-user multiple-input single-output (MISO) downlink system for simultaneous wireless information and power transfer (SWIPT), in which a set of single-antenna mobile stations (MSs) receive information and energy simultaneously via power splitting (PS) from the signal sent by a multi-antenna base station (BS). We aim to minimize the total transmission power at BS by jointly designing transmit beamforming vectors and receive PS ratios for all MSs under their given signal-to-interference-plus-noise ratio (SINR) constraints for information decoding and harvested power constraints for energy harvesting. First, we derive the sufficient and necessary condition for the feasibility of our formulated problem. Next, we solve this non-convex problem by applying the technique of semidefinite relaxation (SDR). We prove that SDR is indeed tight for our problem and thus achieves its global optimum. Finally, we propose two suboptimal solutions of lower complexity than the optimal solution based on the principle of separating the optimization of transmit beamforming and receive PS, where the zero-forcing (ZF) and the SINR-optimal based transmit beamforming schemes are applied, respectively. The concept of deploying a large number of antennas at the base station, often called massive multiple-input multiple-output (MIMO), has drawn considerable interest because of its potential ability to revolutionize current wireless communication systems. Most literature on massive MIMO systems assumes time division duplexing (TDD), although frequency division duplexing (FDD) dominates current cellular systems. Due to the large number of transmit antennas at the base station, currently standardized approaches would require a large percentage of the precious downlink and uplink resources in FDD massive MIMO be used for training signal transmissions and channel state information (CSI) feedback. To reduce the overhead of the downlink training phase, we propose practical open-loop and closed-loop training frameworks in this paper. We assume the base station and the user share a common set of training signals in advance. In open-loop training, the base station transmits training signals in a round-robin manner, and the user successively estimates the current channel using long-term channel statistics such as temporal and spatial correlations and previous channel estimates. In closed-loop training, the user feeds back the best training signal to be sent in the future based on channel prediction and the previously received training signals. With a small amount of feedback from the user to the base station, closed-loop training offers better performance in the data communication phase, especially when the signal-to-noise ratio is low, the number of transmit antennas is large, or prior channel estimates are not accurate at the beginning of the communication setup, all of which would be mostly beneficial for massive MIMO systems. Binary exponential backoff is a randomized protocol for regulating transmissions on a multiple-access broadcast channel. Ethernet, a local-area network, is built upon this protocol. The fundamental theoretical issue is stability: Does the backlog of packets awaiting transmission remain bounded in time, provided the rates of new packet arrivals are small enough? It is assumed n ≥ 2 stations share the channel, each having an infinite buffer where packets accumulate while the station attempts to transmit the first from the buffer. Here, it is established that binary exponential backoff is stable if the sum of the arrival rates is sufficiently small. Detailed results are obtained on which rates lead to stability when n = 2 stations share the channel. In passing, several other results are derived bearing on the efficiency of the conflict resolution process. Simulation results are reported that, in particular, indicate alternative retransmission protocols can significantly improve performance. We consider a Wireless Sensor Network where each sensor device is able to harvest energy from the environment, and randomly accesses the channel to transmit packets of random importance to a fusion center. If a collision occurs, the transmission fails and all packets involved are discarded. We design distributed transmission schemes where each sensor node, based on its own energy level and the importance of its own data packet, decides whether to transmit the packet or remain idle, so as to maximize the network utility, defined as the average long-term aggregate network importance of the data packets successfully reported to the fusion center. Due to the generally non-convex structure of the optimization problem, we resort to approximate solutions. In particular, we use a mathematical artifice based on a game theoretic formulation of the multiaccess problem, where each sensor node is a player that attempts to selfishly maximize the network utility. We characterize the Symmetric Nash Equilibrium (SNE) of this game, where all the sensor nodes employ the same policy. We prove the existence and uniqueness of the SNE, and we show that it is a local maximum of the original optimization problem. Moreover, we derive an algorithm to compute it. The IEEE 802.11 standard for wireless local area networks (WLANs) employs a medium access control (MAC), called distributed coordination function (DCF), which is based on carrier sense multiple access with collision avoidance (CSMA CA). The collision avoidance mechanism utilizes the random backoff prior to each frame transmission attempt. The random nature of the backoff reduces the collision probability, but cannot completely eliminate collisions. It is known that the throughput performance of the 802.11 WLAN is significantly compromised as the number of stations increases. In this paper, we propose a novel distributed reservation-based MAC protocol, called early backoff announcement (EBA), which is backward compatible with the legacy DCF. Under EBA, a station announces its future backoff information in terms of the number of backoff slots via the MAC header of its frame being transmitted. All the stations receiving the information avoid collisions by excluding the same backoff duration when selecting their future backoff value. Through extensive simulations, EBA is found to achieve a significant increase in the throughput performance as well as a higher degree of fairness compared to the 802.11 DCF. In wireless cellular networks and wireless local area networks, nonlinear network utility maximization need to be conducted over both user rates and transmit powers. For each of the three cases considered in this paper, we present an algorithm that converges to the jointly optimal pair of rate vector and power vector. For the simple case when data rates are not limited by interferences, for example in single-cell downlink transmissions, we propose algorithm 1, which is an iterative bidding mechanism between the base station and mobile users, where knowledge about channel conditions and individual user utility functions is only needed locally at each user but not needed at the base station. In the case when data rates are limited by interferences, the utility maximization problem is complicated both by nonlinear coupling between powers and rates, and by interference among powers. Through centralized iterative steps, we propose algorithm 2, which converges to a joint and global optimum over the solution space of rates and powers. We then consider end-to-end transmissions in cellular networks, which traverse both wireless fading channels and many hops of wired links shared by other traffic. There is a tradeoff between attaining air-interface capacity in the wireless hop and controlling congestion in the wired backbone wide area network. We formulate this end-to-end resource allocation problem in such hybrid networks, and present a solution to obtain the Pareto optimal tradeoff between attaining wireless multi-access fading channel capacity and maximizing global network utility.