Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks

The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter

Enabling decentralized wireless index coding in practice

Index coding is a problem in theoretical computer science and network information theory that studies the optimal coding scheme for transmitting multiple messages across a network to receivers with different side information. The ultimate goal of index coding is to reduce transmission time in a communication network by minimizing the number of messages based on shared information. Index coding theory extends to several key engineering problems in network communication including peer to peer communication, distributed broadcast networks, and interference alignment. Although the theoretical connection between index coding and wireless networks is valuable, we focus on finding index coding strategies for a realistic wireless network. More specifically, we investigate how index coding can be applied to an OFDMA downlink network during the retransmission phase. An orthogonal frequency-division multiple access (OFDMA) downlink network is a network where data is sent downward from a designated higher-level transmitter to a group of receiving nodes. In addition, receivers can often decode the other receivers' physical layer signals on the other sub-channels that can be exploited as side information. If this side information is sent back to the transmitter, it can then be coded to cancel the interference in subsequent retransmission phases resulting in fewer retransmission messages. In this report, we explain the coding model and characterize the benefits of index coding for retransmissions within an OFDMA downlink network. In addition, we demonstrate the results of applying this index coding scheme in such network in both simulation and in an active wireless mesh network.Electrical and Computer Engineerin

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments

Cooperative Relaying and Resource Allocation in Future-Generation Cellular Networks

Driven by the significant consumer demand for reliable and high data rate communications, the future-generation cellular systems are expected to employ cutting-edge techniques to improve the service provisioning at substantially reduced costs. Cooperative relaying is one of the primary techniques due to its ability to improve the spectrum utilization by taking advantage of the broadcast nature of wireless signals. This dissertation studies the physical layer cooperative relaying technique and resource allocation schemes in the cooperative cellular networks to improve the spectrum and energy efficiency from the perspectives of downlink transmission, uplink transmission and device-to-device transmission, respectively. For the downlink transmission, we consider an LTE-Advanced cooperative cellular network with the deployment of Type II in-band decode-and-forward relay stations (RSs) to enhance the cell-edge throughput and to extend the coverage area. This type of relays can better exploit the broadcast nature of wireless signals while improving the utilization of existing allocated spectral resources. For such a network, we propose joint orthogonal frequency division multiplexing (OFDM) subcarrier and power allocation schemes to optimize the downlink multi-user transmission efficiency. Firstly, an optimal power dividing method between eNB and RS is proposed to maximize the achievable rate on each subcarrier. Based on this result, we show that the optimal joint resource allocation scheme for maximizing the overall throughput is to allocate each subcarrier to the user with the best channel quality and to distribute power in a water-filling manner. Since the users' Quality of Service (QoS) provision is one of the major design objectives in cellular networks, we further formulate a lexicographical optimization problem to maximize the minimum rate of all users while improving the overall throughput. A sufficient condition for optimality is derived. Due to the complexity of searching for the optimal solution, we then propose an efficient, low-complexity suboptimal joint resource allocation algorithm, which outperforms the existing suboptimal algorithms that simplify the joint design into separate allocation. Both theoretical and numerical analyses demonstrate that our proposed scheme can drastically improve the fairness as well as the overall throughput. As the physical layer uplink transmission technology for LTE-Advanced cellular network is based on single carrier frequency division multiple access (SC-FDMA) with frequency domain equalization (FDE), this dissertation further studies the uplink achievable rate and power allocation to improve the uplink spectrum efficiency in the cellular network. Different from the downlink OFDM system, signals on all subcarriers in the SC-FDMA system are transmitted sequentially rather than in parallel, thus the user's achievable rate is not simply the summation of the rates on all allocated subcarriers. Moreover, each user equipment (UE) has its own transmission power constraint instead of a total power constraint at the base station in the downlink case. Therefore, the uplink resource allocation problem in the LTE-Advanced system is more challenging. To this end, we first derive the achievable rates of the SC-FDMA system with two commonly-used FDE techniques, zero-forcing (ZF) equalization and minimum mean square error (MMSE) equalization, based on the joint superposition coding for cooperative relaying. We then propose optimal power allocation schemes among subcarriers at both UE and RS to maximize the overall throughput of the system. Theoretical analysis and numerical results are provided to demonstrate a significant gain in the system throughput by our proposed power allocation schemes. Besides the physical layer technology, the trend of improving energy efficiency in future cellular networks also motivates the network operators to continuously bring improvements in the entire network infrastructure. Such techniques include efficient base station (BS) redesign, opportunistic transmission such as device-to-device and cognitive radio communications. In the third part of this dissertation, we explore the potentials of employing cooperative relaying in a green device-to-device communication underlaying cellular network to improve the energy efficiency and spectrum utilization of the system. As the green base station is powered by sustainable energy, the design objective is to enhance both sustainability and efficiency of the device-to-device communication. Specifically, we first propose optimal power adaptation schemes to maximize the network spectrum efficiency under two practical power constraints. We then take the dynamics of the charging and discharging processes of the energy buffer at the BS into consideration to ensure the network sustainability. To this end, the energy buffer is modeled as a G/D/1 queue where the input energy has a general distribution. Power allocation schemes are proposed based on the statistics of the energy buffer to further enhance the network efficiency and sustainability. Theoretical analysis and numerical results are presented to demonstrate that our proposed power allocation schemes can improve the network throughput while maintaining the network sustainability at a certain level. Our analyses developed in this dissertation indicate that the cooperative transmission based on cooperative relaying can significantly improve the spectrum efficiency and energy efficiency of the cellular network for downlink transmission, uplink transmission and device-to-device communication. Our proposed cooperative relaying technique and resource allocation schemes can provide efficient solutions to practical design and optimization of future-generation cellular networks

Energy efficient subchannel and power allocation in cooperative VLC systems

This letter studies the energy efficiency (EE) optimization of cooperative visible light communication (VLC) systems while considering the inter-cell interference and the lineof-sight blockage problems. Specifically, the optimization problem of subchannel and power allocation to maximize EE under transmit power budgets and users' minimum rate constraints is considered. The formulated problem turns out to be a difficult nonlinear fractional program for which a low-complexity iterative solution based on fractional programming theory and the quadratic transform approach is proposed. Extensive simulations are conducted to show the efficacy of the proposed scheme over conventional approaches. In addition, the outage analysis and impacts of varying the transmit power and the subchannel bandwidth on the EE performance are investigated.This work was supported by the Natural Science and Engineering Research Council of Canada (NSERC) through its Discovery Program, the Memorial University VPR Program, and the Spanish National Project TERESA-ADA (TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE). The associate editor coordinating the review of this letter and approving it for publication was H. Zhang