Energy-Aware Radio Resource Management in D2D-Enabled Multi-Tier HetNets

Hybrid networks consisting of both millimeter wave (mmWave) and microwave (μW) capabilities are strongly contested for next-generation cellular communications. A similar avenue of current research is device-to-device (D2D) communications, where users establish direct links with each other rather than using central base stations. However, a hybrid network, where D2D transmissions coexist, requires special attention in terms of efficient resource allocation. This paper investigates dynamic resource sharing between network entities in a downlink transmission scheme to maximize energy efficiency (EE) of the cellular users (CUs) served by either (μW) macrocells or mmWave small cells while maintaining a minimum quality-of-service (QoS) for the D2D users. To address this problem, first, a self-adaptive power control mechanism for the D2D pairs is formulated, subject to an interference threshold for the CUs while satisfying their minimum QoS level. Subsequently, an EE optimization problem, which is aimed at maximizing the EE for both CUs and D2D pairs, has been solved. Simulation results demonstrate the effectiveness of our proposed algorithm, which studies the inherent tradeoffs between system EE, system sum rate, and outage probability for various QoS levels and varying densities of D2D pairs and CUs

Recent Advances in Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention from researchers in recent years. It is a promising technique for offloading local traffic from cellular base stations by allowing local devices, in physical proximity, to communicate directly with each other. Furthermore, through relaying, D2D is also a promising approach to enhancing service coverage at cell edges or in black spots. However, there are many challenges to realizing the full benefits of D2D. For one, minimizing the interference between legacy cellular and D2D users operating in underlay mode is still an active research issue. With the 5th generation (5G) communication systems expected to be the main data carrier for the Internet-of-Things (IoT) paradigm, the potential role of D2D and its scalability to support massive IoT devices and their machine-centric (as opposed to human-centric) communications need to be investigated. New challenges have also arisen from new enabling technologies for D2D communications, such as non-orthogonal multiple access (NOMA) and blockchain technologies, which call for new solutions to be proposed. This edited book presents a collection of ten chapters, including one review and nine original research works on addressing many of the aforementioned challenges and beyond

Integrated cellular and device-to-device networks

textDevice-to-device (D2D) networking enables direct discovery and communication between cellular subscribers that are in proximity, thus bypassing the base stations (BSs). In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled broadband communication technology is also required by public safety networks that must function when cellular networks are not available. Integrating D2D into cellular networks, however, poses many challenges and risks to the long-standing cellular architecture, which is centered around the BSs. This dissertation identifies outstanding technical challenges in D2D-enabled cellular networks and addresses them with novel models and fundamental analysis. First, this dissertation develops a baseline hybrid network model consisting of both ad hoc nodes and cellular infrastructure. This model uses Poisson point processes to model the random and unpredictable locations of mobile users. It also captures key features of multicast D2D including multicast receiver heterogeneity and retransmissions while being tractable for analytical purpose. Several important multicast D2D metrics including coverage probability, mean number of covered receivers per multicast session, and multicast throughput are analytically characterized under the proposed model. Second, D2D mode selection which means that a potential D2D pair can switch between direct and cellular modes is incorporated into the hybrid network model. The extended model is applied to study spectrum sharing between cellular and D2D communications. Two spectrum sharing models, overlay and underlay, are investigated under a unified analytical framework. Analytical rate expressions are derived and applied to optimize the design of spectrum sharing. It is found that, from an overall mean-rate perspective, both overlay and underlay bring performance improvements (vs. pure cellular). Third, the single-antenna hybrid network model is extended to multi-antenna transmission to study the interplay between massive MIMO (multi-input multiple-output) and underlaid D2D networking. The spectral efficiency of such multi-antenna hybrid networks is investigated under both perfect and imperfect channel state information (CSI) assumptions. Compared to the case without D2D, there is a loss in cellular spectral efficiency due to D2D underlay. With perfect CSI, the loss can be completely overcome if the number of canceled D2D interfering signals is scaled appropriately. With imperfect CSI, in addition to pilot contamination, a new asymptotic underlay contamination effect arises. Finally, motivated by the fact that transmissions in D2D discovery are usually not or imperfectly synchronized, this dissertation studies the effect of asynchronous multicarrier transmission and proposes a tractable signal-to-interference-plus-noise ratio (SINR) model. The proposed model is used to analytically characterize system-level performance of asynchronous wireless networks. The loss from lack of synchronization is quantified, and several solutions are proposed and compared to mitigate the loss.Electrical and Computer Engineerin

Resource allocation for network-controlled device-to-device communications in LTE-Advanced

Network-controlled device-to-device (D2D) communication allows cellular users to communicate directly, i.e., without passing through the eNodeB, while the latter retains control over resource allocation. This allows the same time–frequency resources to be allocated to spatially separated D2D flows simultaneously, thus increasing the cell throughput. This paper presents a framework for: (1) selecting which communications should use the D2D mode, and when, and (2) allocating resources to D2D and non-D2D users, exploiting reuse for the former. We show that the two problems, although apparently similar, should be kept separate and solved at different timescales in order to avoid problems, such as excessive packet loss. We model both as optimization problems, and propose a heuristic solution to the second, which must be solved at millisecond timescales. Simulation results show that our framework is practically viable, it avoids the problem of packet losses, increases throughput and reduces delays

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

Resource Allocation and Path Selection Strategies for Cognitive Radio Multihop Networks

The next-generation cellular wireless networks will support high data rates and provide quality of service (QoS) for multimedia applications with increased network capacity. Under limited frequency resources, the conventional approach to increase network capacity is to install more base stations (BSs) to exploit spatial reuse. This solution is not very efficient because the cost of the BS transceiver is quite high. An alterna- tive approach is to employ relay stations (RSs) as intermediate nodes to establish multihop communication paths between mobile hosts and their corresponding BSs. Multihop cellular networks (MCN) can potentially enhance coverage, data rates, QoS performance in terms of call block- ing probability, bit error rate, as well as QoS fairness for different users. A number of different architectures, protocols, and analytical models for MCNs have been proposed in the literature where different system aspects were investigated. This thesis aims to present strategies of re- source allocation (RA) and path selection (PS) for cognitive radio (CR) multi-hop communications over a packet-oriented and bit-interleaved- coded OFDM transmission, employing practical modulation and coding schemes. As a promising technology, cognitive radio can be leveraged by the cellular network to increase the overall spectral efciency by allowing additional users in an already crowded spectrum. Here, we assume that a secondary transmitter (ST) adapt his parameters for transmitting to a secondary receiver (SR) or to a relay, over sections of spectrum owned by licensed or primary users (PUs), without harming the quality of service of the latter. This approach is known as underlay. The performance of the system are evaluated in terms of goodput (GP), which is defined as the number of information bits delivered in error free packets per unit of time. It is able to quantify the trade-off between data rate and link reliability, and it is a more suitable metric to quantify the actual perfor- mance of packet-oriented systems, employing practical modulation and coding schemes, respect to the capacity for example. A generic trans- mitter of the network is able to optimize the GP by a proper selection of the transmission parameters, if the channel state information (CSI) are perfect. In most wireless networks, because of channel estimation errors and channel feedback delay, this CSI will not be perfect there- fore any transmitting node only has outdated and imperfect CSI and the channel prediction and as a consequence, a predicted GP (PGP), will be optimized. GP depends on PER that is not easy to calculate for a multi-carrier system and so will be use kESM technique. From here a Local-RA (L-RA) technique and a Sub-Optimal PS (Sub-PS) strategies are formulated for non-cooperative CR multi-hop communications, ex- ploiting xed decode-and-forward (DF) relay nodes (RNs). With these strategies we are able to reduce the signaling over the feedback channel and the computational complexity, compared to the Optimal-RA with Optimal-PS method, paying a very little reduction of GP. Finally we will evaluate whether the increase of the number of relays corresponds to a performance increase

Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks

In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis

Planning Wireless Cellular Networks of Future: Outlook, Challenges and Opportunities

Cell planning (CP) is the most important phase in the life cycle of a cellular system as it determines the operational expenditure, capital expenditure, as well as the long-term performance of the system. Therefore, it is not surprising that CP problems have been studied extensively for the past three decades for all four generations of cellular systems. However, the fact that small cells, a major component of future networks, are anticipated to be deployed in an impromptu fashion makes CP for future networks vis-a-vis 5G a conundrum. Furthermore, in emerging cellular systems that incorporate a variety of different cell sizes and types, heterogeneous networks (HetNets), energy efficiency, self-organizing network features, control and data plane split architectures (CDSA), massive multiple input multiple out (MIMO), coordinated multipoint (CoMP), cloud radio access network, and millimetre-wave-based cells plus the need to support Internet of Things (IoT) and device-to-device (D2D) communication require a major paradigm shift in the way cellular networks have been planned in the past. The objective of this paper is to characterize this paradigm shift by concisely reviewing past developments, analyzing the state-of-the-art challenges, and identifying future trends, challenges, and opportunities in CP in the wake of 5G. More specifically, in this paper, we investigate the problem of planning future cellular networks in detail. To this end, we first provide a brief tutorial on the CP process to identify the peculiarities that make CP one of the most challenging problems in wireless communications. This tutorial is followed by a concise recap of past research in CP. We then review key findings from recent studies that have attempted to address the aforementioned challenges in planning emerging networks. Finally, we discuss the range of technical factors that need to be taken into account while planning future networks and the promising research directions that necessitates the paradigm shift to do so