Computation Alignment: Capacity Approximation without Noise Accumulation

Consider several source nodes communicating across a wireless network to a destination node with the help of several layers of relay nodes. Recent work by Avestimehr et al. has approximated the capacity of this network up to an additive gap. The communication scheme achieving this capacity approximation is based on compress-and-forward, resulting in noise accumulation as the messages traverse the network. As a consequence, the approximation gap increases linearly with the network depth. This paper develops a computation alignment strategy that can approach the capacity of a class of layered, time-varying wireless relay networks up to an approximation gap that is independent of the network depth. This strategy is based on the compute-and-forward framework, which enables relays to decode deterministic functions of the transmitted messages. Alone, compute-and-forward is insufficient to approach the capacity as it incurs a penalty for approximating the wireless channel with complex-valued coefficients by a channel with integer coefficients. Here, this penalty is circumvented by carefully matching channel realizations across time slots to create integer-valued effective channels that are well-suited to compute-and-forward. Unlike prior constant gap results, the approximation gap obtained in this paper also depends closely on the fading statistics, which are assumed to be i.i.d. Rayleigh.Comment: 36 pages, to appear in IEEE Transactions on Information Theor

Performance of Integrated IoT Network with Hybrid mmWave/FSO/THz Backhaul Link

Establishing end-to-end connectivity of Internet of Things (IoT) network with the core for collecting sensing data from remote and hard-to-reach terrains is a challenging task. In this article, we analyze the performance of an IoT network integrated with wireless backhaul link for data collection. We propose a solution that involves a self-configuring protocol for aggregate node (AN) selection in an IoT network, which sends the data packet to an unmanned aerial vehicle (UAV) over radio frequency (RF) channels. We adopt a novel hybrid transmission technique for wireless backhaul employing opportunistic selections combining (OSC) and maximal ratio combining (MRC) that simultaneously transmits the data packet on mmWave (mW), free space optical (FSO), and terahertz (THz) technologies to take advantage of their complementary characteristics. We employ the decode-and-forward (DF) protocol to integrate the IoT and backhaul links and provide physical layer performance assessment using outage probability and average bit-error-rate (BER) under diverse channel conditions. We also develop simplified expressions to gain a better understanding of the system's performance at high signal-to-noise ratio (SNR). We provide computer simulations to compare different wireless backhaul technologies under various channel and SNR scenarios and demonstrate the performance of the data collection using the integrated link.Comment: This work has been submitted to IEEE for possible publicatio

A Survey on Applications of Cache-Aided NOMA

Contrary to orthogonal multiple-access (OMA), non-orthogonal multiple-access (NOMA) schemes can serve a pool of users without exploiting the scarce frequency or time domain resources. This is useful in meeting the future network requirements (5G and beyond systems), such as, low latency, massive connectivity, users' fairness, and high spectral efficiency. On the other hand, content caching restricts duplicate data transmission by storing popular contents in advance at the network edge which reduces data traffic. In this survey, we focus on cache-aided NOMA-based wireless networks which can reap the benefits of both cache and NOMA; switching to NOMA from OMA enables cache-aided networks to push additional files to content servers in parallel and improve the cache hit probability. Beginning with fundamentals of the cache-aided NOMA technology, we summarize the performance goals of cache-aided NOMA systems, present the associated design challenges, and categorize the recent related literature based on their application verticals. Concomitant standardization activities and open research challenges are highlighted as well

Optimizing Resource Allocation with Energy Efficiency and Backhaul Challenges

To meet the requirements of future wireless mobile communication which aims to increase the data rates, coverage and reliability while reducing energy consumption and latency, and also deal with the explosive mobile traffic growth which imposes high demands on backhaul for massive content delivery, developing green communication and reducing the backhaul requirements have become two significant trends. One of the promising techniques to provide green communication is wireless power transfer (WPT) which facilitates energy-efficient architectures, e.g. simultaneous wireless information and power transfer (SWIPT). Edge caching, on the other side, brings content closer to the users by storing popular content in caches installed at the network edge to reduce peak-time traffic, backhaul cost and latency. In this thesis, we focus on the resource allocation technology for emerging network architectures, i.e. the SWIPT-enabled multiple-antenna systems and cache-enabled cellular systems, to tackle the challenges of limited resources such as insufficient energy supply and backhaul capacity. We start with the joint design of beamforming and power transfer ratios for SWIPT in MISO broadcast channels and MIMO relay systems, respectively, aiming for maximizing the energy efficiency subject to both the Quality of Service (QoS) constraints and energy harvesting constraints. Then move to the content placement optimization for cache-enabled heterogeneous small cell networks so as to minimize the backhaul requirements. In particular, we enable multicast content delivery and cooperative content sharing utilizing maximum distance separable (MDS) codes to provide further caching gains. Both analysis and simulation results are provided throughout the thesis to demonstrate the benefits of the proposed algorithms over the state-of-the-art methods

マクロセルにオーバーレイするスモールセルのための層間干渉低減に関する研究

The huge number of mobile terminals in use and the radio frequency scarceness are the relevant issues for future wireless communications. Frequency sharing has been considered to solve the problem. Addressing the issues has led to a wide adoption of small cell networks particularly femtocells overlaid onto macrocell or small cells implemented with the support of distributed antenna systems (DASs). Small cell networks improve link quality and frequency reuse. Spectrum sharing improves the usage efficiency of the licensed spectrum. A macrocell underlaid with femtocells constitutes a typical two-tier network for improving spectral efficiency and indoor coverage in a spectrum sharing environment. Considering the end-user access control over the small cell base station (SBS), with shared usage of the macrocell’s spectrum, this dissertation contribution is an investigation of mitigation techniques of crosstier interference. Such cross-tier interference mitigation leads to possible implementation of multi-tier and heterogeneous networks. The above arguments underpin our work which is presented in the hereby dissertation. The contributions in this thesis are three-fold. Our first contribution is an interference cancellation scheme based on the transmitter symbols fed back to the femtocell base station (FBS) undergoing harmful cross-tier interference. We propose a cross-tier interference management between the FBS and the macrocell base station (MBS) in uplink communications. Our proposal uses the network infrastructure for interference cancellation at the FBS. Besides, we profit from terminal discovery to derive the interference level from the femtocell to the macrocell. Thus, additionally, we propose an interference avoidance method based on power control without cooperation from the MBS. In our second contribution, we dismiss the use of the MBS for symbol feedback due to delay issues. In a multi-tier cellular communication system, the interference from one tier to another, denoted as cross-tier interference, is a limiting factor for the system performance. In spectrum-sharing usage, we consider the uplink cross-tier interference management of heterogeneous networks using femtocells overlaid onto the macrocell. We propose a variation of the cellular architecture and introduce a novel femtocell clustering based on interference cancellation to enhance the sum rate capacity. Our proposal is to use a DAS as an interface to mitigate the cross-tier interference between the macrocell and femtocell tiers. In addition, the DAS can forward the recovered data to the macrocell base station (MBS); thus, the macrocell user can reduce its transmit power to reach a remote antenna unit (RAU) located closer than the MBS. By distributing the RAUs within the macrocell coverage, the proposed scheme can mitigate the cross-tier interference at different locations for several femtocell clusters. Finally, we address the issue of cross-tier interference mitigation in heterogeneous cognitive small cell networks comparing equal and unequal signal-to-noise ratio (SNR) branches in multi-input multi-output (MIMO) Alamouti scheme. Small cell networks enhance spectrum efficiency by handling the indoor traffic of mobile networks on a frequency-reuse operation. Because most of the current mobile traffic happens indoor, we introduce a prioritization shift by imposing a threshold on the outage generated by the outdoor mobile system to the indoor small cells. New closed-form expressions are derived to validate the proposed bit error rate (BER) function used in our optimization algorithm. We propose a joint transmit antenna selection and power allocation which minimizes the proposed BER function of the outdoor mobile terminal. The optimization is constrained by the outage at the small cell located near the cooperating transmit relays. Such constraint improves the initialization of the iterative algorithm compared to randomly choosing initial points. The proposed optimization yields a dynamic selection of the relays with power control pertaining to the outdoor mobile terminal performance.電気通信大学201

System design issues in dense urban millimeter wave cellular networks

Upcoming deployments of cellular networks will see an increasing use of millimeter wave (mmWave) frequencies, roughly between 20-100 GHz. The goal of this dissertation is to investigate some key design issues in dense urban mmWave cellular networks by developing mathematical models that are representative of these networks. In the first contribution, stochastic geometry (SG) is used to study the per user rate performance of multi-user MIMO (MU-MIMO) in downlink mmWave cellular network incorporating the impact of a spatially sparse blockage dependent multipath channel and hybrid precoding. Performance of MU-MIMO is then compared with single-user beamforming and spatial multiplexing in different network scenarios considering coverage, rate and power consumption tradeoffs to suggest when to use which MIMO scheme. The second contribution reconsiders a popular received signal power model used in system capacity analysis of MIMO wireless networks employing single user beamforming. A modification is suggested to the model by introducing a correction factor. An approximate analysis is done to justify incorporating such a factor and simulations are performed to validate it's importance. Although this contribution does not study a new system design issue for mmWave cellular, it highlights a shortcoming with using the popular received signal power model to study design issues in mmWave cellular networks. The third and fourth contributions investigate resource allocation in self-backhauled mmWave cellular networks. In order to enable affordable initial deployments of mmWave cellular, self-backhauling is envisioned as a cost-saving solution. The third contribution investigates how to divide resources between uplink and downlink for access and backhaul in self-backhauled networks with single hop wireless backhauling. The performance of dynamic time division duplexing (TDD) and integrated access-backhaul (IAB) is compared with static TDD and orthogonal access backhaul (OAB) strategies using a SG based model. The last contribution of this dissertation addresses the following key question for self-backhauled networks. What is the maximum extended coverage area that a single fiber site can support using multi-hop relaying, while still achieving a minimum target per user data rate? The problem of maximizing minimum per user rates is studied considering a series of deployments with a single fiber site and varying number of relays. Several design guidelines for multi-hop mmWave cellular networks are provided based on the analytical and empirical results.Electrical and Computer Engineerin

Delay QoS Provisioning and Optimal Resource Allocation for Wireless Networks

Recent years have witnessed a significant growth in wireless communication and networking due to the exponential growth in mobile applications and smart devices, fueling unprecedented increase in both mobile data traffic and energy demand. Among such data traffic, real-time data transmissions in wireless systems require certain quality of service (QoS) constraints e.g., in terms of delay, buffer overflow or packet drop/loss probabilities, so that acceptable performance levels can be guaranteed for the end-users, especially in delay sensitive scenarios, such as live video transmission, interactive video (e.g., teleconferencing), and mobile online gaming. With this motivation, statistical queuing constraints are considered in this thesis, imposed as limitations on the decay rate of buffer overflow probabilities. In particular, the throughput and energy efficiency of different types of wireless network models are analyzed under QoS constraints, and optimal resource allocation algorithms are proposed to maximize the throughput or minimize the delay. In the first part of the thesis, the throughput and energy efficiency analysis for hybrid automatic repeat request (HARQ) protocols are conducted under QoS constraints. Approximations are employed for small QoS exponent values in order to obtain closed-form expressions for the throughput and energy efficiency metrics. Also, the impact of random arrivals, deadline constraints, outage probability and QoS constraints are studied. For the same system setting, the throughput of HARQ system is also analyzed using a recurrence approach, which provides more accurate results for any value of the QoS exponent. Similarly, random arrival models and deadline constraints are considered, and these results are further extended to the finite-blocklength coding regime. Next, cooperative relay networks are considered under QoS constraints. Specifically, the throughput performance in the two-hop relay channel, two-way relay channel, and multi-source multi-destination relay networks is analyzed. Finite-blocklength codes are considered for the two-hop relay channel, and optimization over the error probabilities is investigated. For the multi-source multi-destination relay network model, the throughput for both cases of with and without CSI at the transmitter sides is studied. When there is perfect CSI at the transmitter, transmission rates can be varied according to instantaneous channel conditions. When CSI is not available at the transmitter side, transmissions are performed at fixed rates, and decoding failures lead to retransmission requests via an ARQ protocol. Following the analysis of cooperative networks, the performance of both half-duplex and full-duplex operations is studied for the two-way multiple input multiple output (MIMO) system under QoS constraints. In full-duplex mode, the self-interference inflicted on the reception of a user due to simultaneous transmissions from the same user is taken into account. In this setting, the system throughput is formulated by considering the sum of the effective capacities of the users in both half-duplex and full-duplex modes. The low signal to noise ratio (SNR) regime is considered and the optimal transmission/power-allocation strategies are characterized by identifying the optimal input covariance matrices. Next, mode selection and resource allocation for device-to-device (D2D) cellular networks are studied. As the starting point, ransmission mode selection and resource allocation are analyzed for a time-division multiplexed (TDM) cellular network with one cellular user, one base station, and a pair of D2D users under rate and QoS constraints. For a more complicated setting with multiple cellular and D2D users, two joint mode selection and resource allocation algorithms are proposed. In the first algorithm, the channel allocation problem is formulated as a maximum-weight matching problem, which can be solved by employing the Hungarian algorithm. In the second algorithm, the problem is divided into three subproblems, namely user partition, power allocation and channel assignment, and a novel three-step method is proposed by combining the algorithms designed for the three subproblems. In the final part of the thesis, resource allocation algorithms are investigated for content delivery over wireless networks. Three different systems are considered. Initially, a caching algorithm is designed, which minimizes the average delay of a single-cell network. The proposed algorithm is applicable in settings with very general popularity models, with no assumptions on how file popularity varies among different users, and this algorithm is further extended to a more general setting, in which the system parameters and the distributions of channel fading change over time. Next, for D2D cellular networks operating under deadline constraints, a scheduling algorithm is designed, which manages mode selection, channel allocation and power maximization with acceptable complexity. This proposed scheduling algorithm is designed based on the convex delay cost method for a D2D cellular network with deadline constraints in an OFDMA setting. Power optimization algorithms are proposed for all possible modes, based on our utility definition. Finally, a two-step intercell interference (ICI)-aware scheduling algorithm is proposed for cloud radio access networks (C-RANs), which performs user grouping and resource allocation with the goal of minimizing delay violation probability. A novel user grouping algorithm is developed for the user grouping step, which controls the interference among the users in the same group, and the channel assignment problem is formulated as a maximum-weight matching problem in the second step, which can be solved using standard algorithms in graph theory