On Capacity of Wireless Networks Using Practical Directional Antennas

Transmission power plays a crucial role in the design and performance of wireless networks. The issue is therefore complex since an increase in transmission power implies that a high quality signal is received at the receiver and hence an increase in channel capacity. Conversely, due to the shared nature of the wireless medium an increase in transmission power also implies high interference in the surrounding region and hence a quadratic reduction in the capacity of wireless networks. Recent literatures indicate that employing multiple channels can mitigate the negative effects of wireless interference and thus greatly improve the overall network capacity. Therefore, it is worth investigating the effect of exploiting power on the capacity of multi-channel multi-radio (MC-MR) wireless networks. Specifically, in this paper we address the following questions: (a) Can we maximize the capacity of MC-MR wireless networks by exploiting power? (b) Under what criteria can we increase the transmission power of the nodes in a MC-MR network? %In this paper, we address these issues and investigate the impact of employing high transmission power and multiple channels in a static wireless network when node placements are chosen arbitrarily. When $n$ nodes each with $m$ half-duplex interfaces are optimally deployed in a torus of unit area, traffic patterns are optimally assigned, each transmission's range is optimally chosen and in the presence of $c$ channels, we show that in contrast to the setting where nodes transmit at minimum power level $P_0$ the transport capacity, measured in bit-meters per second, of MC-MR network exploiting power is increased by $\Theta(\frac{c}{c_{min}})$ in region $c_{min} mn/2$ when nodes tune to transmit power level of $P_0(\frac{c}{c_{min}})^(\frac{\alpha}{2})$ and $P_0n^{\frac{\alpha}{2}}$ respectively. Where $c_{min}$ is the minimum number of channels required to achieve conflict-free transmissions in a network. Our analysis also sheds light into several insights that designers may want to consider to improve the performance of energy-efficient bandwidth-constrained wireless networks.

We present the first unified modeling framework for the computation of the throughput capacity of random wireless ad hoc networks in which information is disseminated by means of unicast routing, multicast routing, broadcasting, or different forms of anycasting. We introduce (n,m, k)-casting as a generalization of all forms of one-to-one, one-to-many and many-to-many information dissemination in wireless networks. In this context, n, m, and k denote the total number of nodes in the network, the number of destinations for each communication group, and the actual number of communication-group members that receive information (i.e., k lesm), respectively. We compute upper and lower bounds for the (n, m, k)- cast throughput capacity in random wireless networks. When m = k = ominus(1), the resulting capacity equals the well-known capacity result for multi-pair unicasting by Gupta and Kumar. We demonstrate that ominus(1/radic(mnlogn)) bits per second constitutes a tight bound for the capacity of multicasting (i.e., m = k < n) when m les ominus (n/(log n)). We show that the multicast capacity of a wireless network equals its capacity for multi-pair unicasting when the number of destinations per multicast source is not a function of n. We also show that the multicast capacity of a random wireless ad hoc network is ominus (1/n), which is the broadcast capacity of the network, when m ges ominus(n/ log n). Furthermore, we show that ominus (radicm/(kradic(n log n))),ominus(1/(k log n)) and ominus(1/n) bits per second constitutes a tight bound for the throughput capacity of multicasting (i.e., k < m < n) when ominus(1) les m les ominus (n/ log n), k les ominus(n / log n) les m les n and ominus (n/ log n) les k les m les n respectively.

Abstract—We study the capacity of a large-scale random wireless network for multicast. Assume that n wireless nodes are uniformly randomly deployed in a square region with sidelength a and all nodes have the uniform transmission range r and uniform interference range R&amp;gt; r. We further assume that each wireless node can transmit (or receive) at W bits/second over a common wireless channel. For each node vi, we randomly and independently pick k − 1 points pi,j (1 ≤ j ≤ k − 1) from the square, and then multicast data to the nearest node for each pi,j. The aggregated multicast capacity is defined as the total data rate of all multicast sessions in the network. We derive matching asymptotic upper bounds and lower bounds on multicast capacity of random wireless networks. Under protocol interference model, when a 2 /r 2 = �O(n / log(n)), we show that the total multicast n capacity is Θ ( log n · W √ ) when k = O( k n); the total multicast log n capacity is Θ(W) when k = Ω ( n log n Xiang-Yang Li, Associate Member, IEEE,). Our bounds unify the previous capacity bounds on unicast (when k = 2) by Gupta and Kumar [6] and broadcast (when k = n) in [9], [20]. We also study the capacity of group-multicast for wireless networks where for each source node, we randomly select k − 1 groups of nodes as receivers and the nodes in each group are within a constant hops from the group leader. The same asymptotic upper bounds and lower bounds still hold. We also extend our capacity bounds to d-dimensional networks. Index Terms—Wireless ad hoc networks, capacity, multicast, broadcast, unicast, scheduling, optimization, VC dimension. I.

The increasing use of multi-hop wireless networks and the growing demand of bandwidth-intensive multimedia applications are the driving force to explore innovative techniques that can enhance the capacity of multi-hop wireless networks. The commonly used omni-directional antennas limit the spatial reusability of the wireless channel and hence reduce the available capacity of wireless networks. On the contrary, bandforming antennas, that enable directional transmissions and receptions, can overcome the aforementioned limitation. With the recent advances in signed processing and antenna technologies, smart beamforming antennas have become feasible in compact sizes and suitable prices and hence pertinent to multi-hop wireless networks. However, lack of appropriate control over the antenna beamforming may deteriorate the overall performance even below the level achieved by omni-directional antennas. Moreover, beamforming antennas introduce unprecedented challenges including deafness and directional hidden terminal problems. Hence, it is important to design efficient mechanisms for both Medium Access Control (MAC) and routing to deal with these challenges that hinder the full exploitation of spatial reusability offered by smart beamforming antennas. In this dissertation, we develop an analytical framework for modeling directional contention-based MAC protocols, which is, up to our knowledge, the first model to include deafness in the analysis. We show that deafness can severely limit the network capacity. Based on the insights gained from our analysis of the limitations of the existing solutions, we propose a novel opportunistic directional MAC protocol for multi-hop wireless networks with beamforming antennas. The proposed MAC protocol employs a new backoff mechanism that aims at minimizing the unnecessary idle waiting time, which is a key factor in leveraging the spatial reuse. Through extensive simulations, we demonstrate that the proposed MAC protocol enhances the performance in terms of throughput, delay, packet delivery ratio and fairness. We have also addressed the question about the theoretical capacity gain achieved by beamforming antennas. We derive a generic interference model that can accommodate any antenna radiation pattern and show that the capacity gain is significant even when realistic antenna radiation patterns are used. Since smart beamforming antennas can significantly spare the network resources, they can be utilized to provide Quality of Service (QoS) guarantees. We study the bandwidth-guaranteed routing problem in contention-based multi-hop wireless networks with beamforming antennas. We first present an analysis for the wireless links interdependencies in a contention-based environment in the presence of beamforming, which helps in our formulation of the QoS routing problem as a mixed-integer non-linear optimization problem. We then propose a routing and admission control algorithm for its solution. Our simulation results demonstrate the accuracy of our analysis and the ability of our proposed algorithm to find bandwidth-guaranteed routes. In summary, the analysis and design approaches, adopted in this dissertation, enhance the throughput of multi-hop wireless networks by grasping the transmission opportunities offered by smart beamforming antennas while dealing with the beamforming-related challenges at the MAC and network layers, which otherwise limit the spatial reusability of the wireless channel.

The throughput capacity of arbitrary wireless networks under the physical Signal to Interference Plus Noise Ratio (SINR) model has received much attention in recent years. In this paper, we investigate the question of how much the worst-case performance of uniform and non-uniform power assignments differ under constraints such as a bound on the area where nodes are distributed or restrictions on the maximum power available. We determine the maximum factor by which a non-uniform power assignment can outperform the uniform case in the SINR model. More precisely, we prove that in one-dimensional settings the capacity of a non-uniform assignment exceeds a uniform assignment by at most a factor of O(logL max ) when the length of the network is L max . In two-dimensional settings, the uniform assignment is at most a factor of O(logP max ) worse than the non-uniform assignment if the maximum power is P max . We provide algorithms that reach this capacity in both cases. Due to lower bound examples in previous work, these results are tight in the sense that there are networks where the lack of power control causes a performance loss in the order of these factors. As a consequence, engineers and researchers may prefer the uniform model due to its simplicity if this degree of performance deterioration is acceptable.

Full-duplex (FD) wireless communication improves the attainable spectral efficiency of the wireless network with the simultaneous transmission and reception over the same frequency channel at a single timeslot. However, the effect of self-interference (SI) and inter-user interference (IUI) become crucial to take into consideration compared to the current half-duplex system. Many researches have been studied to suppress the SI and IUI, to design the medium access control (MAC) protocol, and to propose resource management techniques for realizing the FD system and truly achieving the double transmission capacity in the network. In this paper, we propose a novel FD MAC protocol with a mixture of concurrent and sequential transmission scheme, namely FD-MCST, for maximizing the transmission capacity in multihop wireless networks. Through FD-MCST, the transmitting node can cooperatively share the transmission capacity status for maximizing the network capacity. As a result, numerical simulations reveal that the proposed FD-MCST can accomplish a higher achievable network capacity of up to 1.7 times and nearly twice the achievable throughput with a reasonable amount of achievable transmission overhead about 7.7%, compared to the existing FD MAC protocols.

Proposing a centralized algorithm to minimize message broadcasting energy in wireless sensor networks using directional antennas

A suburban ad-hoc network (SAHN) interconnects a cooperative group at broadband speed using wireless links. The nodes are stationary. A SAHN involves low installation and service costs for SAHN specific traffic. Some current routing solutions for mobile ad-hoc networks may be used in the SAHN after certain optimizations. Efficiency can be improved by using smart directional antennas. Neighboring nodes falling outside the transmission region of a directional antenna are less vulnerable to co-channel interference. Additionally, increased transmission range can be achieved by reducing noise, interference and multipath fading. We emphasize the interference reduction capability of directional antennas and investigate the routing performances using three antenna schemes; multiple fixed directional, multiple omnidirectional and single omnidirectional antennas. We present an estimate of the achievable performance in a SAHN through extensive simulations. We also discuss the impact of using omnidirectional antennas on routing performance where different networks, using overlapping frequency channels, exist within each other's transmission ranges.

We study the multicast capacity of large-scale random extended multihop wireless networks, where a number of wireless nodes are randomly located in a square region with side length <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</i> = √ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> , by use of Poisson distribution with density 1. All nodes transmit at a constant power <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> , and the power decays with attenuation exponent <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">α &gt; 2</i> . The data rate of a transmission is determined by the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SINR</i> as <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i> log(1+ SINR), where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i> is the bandwidth. There are <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns</i> randomly and independently chosen multicast sessions. Each multicast session has <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> randomly chosen terminals. We show that when <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> ≤ θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> [( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> )/((log <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2α+ 6</sup> )] and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns</i> ≥ θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/2+β</sup> , the capacity that each multicast session can achieve, with high probability, is at least <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">8</sub> [(√ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> )/( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns</i> √ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> )], where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">8</sub> are some special constants and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">β &gt; 0</i> is any positive real number. We also show that for <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> = <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ( [( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> )/(log <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> )]) , the per-flow multicast capacity under Gaussian channel is at most <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> ([(√ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> )/( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns</i> √ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> )]) when we have at least <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ns</i> = Ω(log <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ) random multicast flows. Our result generalizes the unicast capacity for random networks using percolation theory.

The new ICRH antenna planned for the Enhanced Performance phase of JET (JET-EP) is analyzed using the antenna coupling code ICANT, which self-consistently determines the currents on all antenna parts. This study addresses, using a simplified antenna model, the question of the impact on the coupling of the poloidal segmentation of the conductors, of their width and of their poloidal phasing. We also address the question of the relation between the imaginary part of the power computed by the code and the input impedance of the antenna. An example of current distribution on the complete antenna in vacuum is also shown.

Since fast transients such as fast radio bursts are short-duration events, the telescope should require a wide instantaneous field of view (FoV). Unlike the traditional beam-scanning technology, this letter proposes a new approach for transient radio target detection using focal-field feature matching. Based on the off-axis focusing characteristics of the parabolic antenna reflector, the focal-field distribution (FFD) database is established on the basis of various incident angles and frequencies. Combining the frequency feature of the transients, an improved compressed sensing method using the multiple-frequency joint estimation is proposed. The direction of the transients can be identified through the relationship of the reconstructed index and FFD feature database. Moreover, according to the received energy distribution, a database-selection method is proposed as a preprocessing to reduce the algorithm complexity. A simplified antenna model is used to generate the FFD database. The simulation results demonstrate that this approach can accurately estimate the transient position. In addition, compared with the traditional multibeam scanning system, the proposed method increases the FoV of the radio telescope and can provide an extended detection for transients.

In order to excite fast wave in the ion cyclotron range of frequencies (ICRF) using multiple antennas with the phase difference in the Large Helical Device (LHD), a controllable wavenumber antenna that consists of two single-strap antennas is designed, and the electrical characteristic features of the antenna are estimated by using a three-dimensional electromagnetic commercial code and the simplified antenna model. Controlling the radio-frequency (RF) phase difference between these two single-straps, reverse-phase excitation can be achieved in order to reduce the impurity production. According to this estimate, the RF current profile on the strap surface is strongly concentrated on the both horizontal strap edges, and the electrical strap length at frequency of 85 MHz is longer than the quarter wavelength of 85 MHz (λ85 MHz/4). Excitable wavenumber spectra are different in various RF phases and frequencies. At the low frequencies (< 60 MHz) with in-phase, effective wavenumbers between k = 0 m−1 and k = 10 m−1 can be excited. During the reverse-phase excitation, large (k = 6, 15 m−1) wavenumber spectra with low (k = 0 m−1) wavenumber kept small are obtained.

In this paper we present a method to assess measurements for link quality estimation in wireless networks. Quality of service (QoS) is increasingly important in 3G wireless networks. Commonly, the end to end QoS is defined by delay and error rate. To meet the end-to-end QoS requirements it is very important to control the error rates on the air interface. The error rates can be controlled by change the energy per bit on the air interface. A mismatching energy assignment will either result in a waste of capacity or in a violation of the error rate requirements for the air interface. Thus, the link quality estimation is critical for performance and capacity of wireless networks. In this paper we present a method to evaluate the value of possible measurements for link quality estimation. This method supports the selection process of appropriate measurements and allows the comparison of their performance. As an example, we apply the presented method to an UMTS 12.2 kbps connection.

Since the unlicensed 60 GHz band has the extensively wide continuous spectrum and its corresponding millimeter-wave signal has high directivity gain, the 60 GHz band is a good option for the broadband wireless mesh networks. This paper focuses on link scheduling and routing over the 60 GHz multi-channel wireless mesh networks, where each mesh router has multiple radios and multiple directional antennas. We formulate a linear programming based framework, which incorporates multi-channel and multi-radio, directional antenna, and 60 GHz millimeter-wave communications, to model the network throughput of the directional antenna based 60 GHz mesh networks. Under this framework, we derive the solution to the problem of maximizing the network throughput subject to the fairness constraint and the directional-antenna based wireless channel interference constraint. Then, we design a heuristic joint link scheduling and routing scheme which aims at approximately attaining the optimal solution to the joint optimization problem under our proposed framework. We conduct extensive simulations to validate and evaluate our proposed scheme.

Anypath routing is proposed to improve the performance of wireless networks by exploiting the spatial diversity and broadcast nature of the wireless medium. In this paper, we study anypath routing in wireless networks with directional antennas, and propose DART (Directional Anypath RouTing), a crosslayer design of MAC and routing layers. For the routing layer, we propose two shortest directional anypath routing algorithms based on two antenna models. Our routing algorithms are simple and fast, thus are suitable for implementation in practical protocols. For the MAC layer, we present a directional anycast MAC, which is an enhancement to the IEEE 802.11 MAC, making DART suitable for integration into current systems. Simulation results show that DART can significantly reduce the packet transmission delay.