Performance evaluation of cross-layer energy-efficient transmit antenna selection for spatial multiplexing systems

Abstract Multiple-input multiple-output (MIMO) and cognitive radio (CR) are key techniques for present and future high-speed wireless technologies. On the other hand, there are rising energy costs and greenhouse emissions associated with the provision of high-speed wireless communications. Consequently, the design of high-speed energy efficient systems is paramount for next-generation wireless systems. This thesis studies energy-efficient antenna selection for spatial multiplexing multiple-antenna systems from a cross-layer perspective, contrary to the norm, where physical-layer energy efficiency metrics are optimized. The enhanced system performance achieved by cross-layer designs in wireless networks motivates this research. The aim of the thesis is to propose and analyze novel cross-layer energy-efficient transmit antenna selection schemes that enhance energy efficiency and system performance - with regard to throughput, transmission latency, packet error rate and receiver buffer requirements. Firstly, this thesis derives the analytical expression for data link throughput for point-to-point spatial multiplexing multiple-antenna systems - which include MIMO and underlay CR MIMO systems - equipped with linear receivers with N-process stop-and-wait (N-SAW) as the automatic repeat request (ARQ) protocol. The performance of cross-layer transmit antenna selection, which maximizes the derived throughput metric, is then analyzed. The impact of packet size, number of SAW processes and the stalling of packets inside the receiver reordering buffer is considered in the investigation. The results show that the cross-layer approach, which takes into account system characteristics at both the data link and physical layers, has superior performance in comparison with the conventional physical-layer approach, which optimizes capacity. Secondly, this thesis proposes a cross-layer energy efficiency metric, based on the derived system throughput. Energy-efficient transmit antenna selection for spatial multiplexing MIMO systems, which maximizes the proposed cross-layer energy efficiency metric, by jointly optimizing the transmit antenna subset and transmit power, subject to spectral efficiency and transmit power constraints, is then introduced and analyzed. Additionally, adaptive modulation is incorporated into the proposed cross-layer scheme to enhance system performance. Cross-layer energyefficient transmit antenna selection for underlay CR MIMO systems, where interference constraints now come into play, is then considered. Lastly, this thesis develops novel reduced complexity versions of the proposed cross-layer energyefficient transmit antenna selection schemes - along with detailed complexity analysis - which shows that the proposed cross-layer approach attains significant energy efficiency and performance gains at affordable computational complexity

Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks

Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum. This has motivated the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques. In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies

Studies on efficient spectrum sharing in coexisting wireless networks.

Wireless communication is facing serious challenges worldwide: the severe spectrum shortage along with the explosive increase of the wireless communication demands. Moreover, different communication networks may coexist in the same geographical area. By allowing multiple communication networks cooperatively or opportunistically sharing the same frequency will potentially enhance the spectrum efficiency. This dissertation aims to investigate important spectrum sharing schemes for coexisting networks. For coexisting networks operating in interweave cognitive radio mode, most existing works focus on the secondary network’s spectrum sensing and accessing schemes. However, the primary network can be selfish and tends to use up all the frequency resource. In this dissertation, a novel optimization scheme is proposed to let primary network maximally release unnecessary frequency resource for secondary networks. The optimization problems are formulated for both uplink and downlink orthogonal frequency-division multiple access (OFDMA)-based primary networks, and near optimal algorithms are proposed as well. For coexisting networks in the underlay cognitive radio mode, this work focuses on the resource allocation in distributed secondary networks as long as the primary network’s rate constraint can be met. Global optimal multicarrier discrete distributed (MCDD) algorithm and suboptimal Gibbs sampler based Lagrangian algorithm (GSLA) are proposed to solve the problem distributively. Regarding to the dirty paper coding (DPC)-based system where multiple networks share the common transmitter, this dissertation focuses on its fundamental performance analysis from information theoretic point of view. Time division multiple access (TDMA) as an orthogonal frequency sharing scheme is also investigated for comparison purpose. Specifically, the delay sensitive quality of service (QoS) requirements are incorporated by considering effective capacity in fast fading and outage capacity in slow fading. The performance metrics in low signal to noise ratio (SNR) regime and high SNR regime are obtained in closed forms followed by the detailed performance analysis

Relay assisted device-to-device communication with channel uncertainty

The gains of direct communication between user equipment in a network may not be fully realised due to the separation between the user equipment and due to the fading that the channel between these user equipment experiences. In order to fully realise the gains that direct (device-to-device) communication promises, idle user equipment can be exploited to serve as relays to enforce device-to-device communication. The availability of potential relay user equipment creates a problem: a way to select the relay user equipment. Moreover, unlike infrastructure relays, user equipment are carried around by people and these users are self-interested. Thus the problem of relay selection goes beyond choosing which device to assist in relayed communication but catering for user self-interest. Another problem in wireless communication is the unavailability of perfect channel state information. This reality creates uncertainty in the channel and so in designing selection algorithms, channel uncertainty awareness needs to be a consideration. Therefore the work in this thesis considers the design of relay user equipment selection algorithms that are not only device centric but that are relay user equipment centric. Furthermore, the designed algorithms are channel uncertainty aware. Firstly, a stable matching based relay user equipment selection algorithm is put forward for underlay device-to-device communication. A channel uncertainty aware approach is proposed to cater to imperfect channel state information at the devices. The algorithm is combined with a rate based mode selection algorithm. Next, to cater to the queue state at the relay user equipment, a cross-layer selection algorithm is proposed for a twoway decode and forward relay set up. The algorithm proposed employs deterministic uncertainty constraint in the interference channel, solving the selection algorithm in a heuristic fashion. Then a cluster head selection algorithm is proposed for device-to-device group communication constrained by channel uncertainty in the interference channel. The formulated rate maximization problem is solved for deterministic and probabilistic constraint scenarios, and the problem extended to a multiple-input single-out scenario for which robust beamforming was designed. Finally, relay utility and social distance based selection algorithms are proposed for full duplex decode and forward device-to-device communication set up. A worst-case approach is proposed for a full channel uncertainty scenario. The results from computer simulations indicate that the proposed algorithms offer spectral efficiency, fairness and energy efficiency gains. The results also showed clearly the deterioration in the performance of networks when perfect channel state information is assumed