Daniel K. C. So

Resource Efficiency: A New Paradigm on Energy Efficiency and Spectral Efficiency Tradeoff

Spectral efficiency (SE) and energy efficiency (EE) are the main metrics for designing wireless networks. Rather than focusing on either SE or EE separately, recent works have focused on the relationship between EE and SE and provided good insight into the joint EE-SE tradeoff. However, such works have assumed that the bandwidth was fully occupied regardless of the transmission requirements and therefore are only valid for this type of scenario. In this paper, we propose a new paradigm for EE-SE tradeoff, namely the resource efficiency (RE) for orthogonal frequency division multiple access (OFDMA) cellular network in which we take into consideration different transmission-bandwidth requirements. We analyse the properties of the proposed RE and prove that it is capable of exploiting the tradeoff between EE and SE by balancing consumption power and occupied bandwidth; hence simultaneously optimizing both EE and SE. We then formulate the generalized RE optimization problem with guaranteed quality of service (QoS) and provide a gradient based optimal power adaptation scheme to solve it. We also provide an upper bound near optimal method to jointly solve the optimization problem. Furthermore, a low-complexity suboptimal algorithm based on a uniform power allocation scheme is proposed to reduce the complexity. Numerical results confirm the analytical findings and demonstrate the effectiveness of the proposed resource allocation schemes for efficient resource usage.

Exact SINR Statistics in the Presence of Heterogeneous Interferers

We derive new results for the higher order moments of signal-to-interference-plus-noise ratio (SINR) in the presence of an arbitrary Poisson point process (PPP)-based heterogeneous interference field. The analysis leverages on a moment-generating-function (MGF) methodology, which only requires the statistics of intended signal and aggregate interference, thus eliminating the need for the exact distribution of SINR. We extend the existing results on interference statistics by deriving a generalized closed-form expression of the interference MGF considering Nakagami-m fading channels with exclusion region. In certain special cases, explicit expressions for the averages of different functions of SINR are found, which also lead to closed-form solutions for the probability distributions of aggregate interference reciprocal and signal-to-interference ratio. We prove that in such cases the effect of total PPP-based interference power on useful transmission is mathematically equivalent to the severe fluctuations from a one-sided Gaussian fading channel. As an application example, the proposed methodology is used together with stochastic geometry theory to characterize the average SINR and rate in heterogeneous cellular networks. The validity of our analytical derivations is confirmed via Monte Carlo simulations for various system settings. We show that with cellular network densification there exists a tradeoff between the average SINR and rate performance.

Hybrid Overlay/Underlay Cognitive Radio Network With MC-CDMA

Cognitive radio allows secondary users (SUs) to exploit the underutilized radio spectrum of the primary networks. To fully utilize the primary spectrum and maximize spectral efficiency, overlay and underlay transmissions, which exploit the white and gray spaces, respectively, should be used together. However, for underlay, the SUs need to transmit at low power to avoid causing harmful interference to the primary users (PUs), whereas the PUs will cause high interference to the SUs. Thus, interference mitigation is a major issue in underlay spectrum utilization. In this paper, a hybrid transmission system that exploits both overlay and underlay is proposed using multicarrier code-division multiple access due to its interference rejection and diversity exploitation capabilities. Unlike existing approaches, which separate the use of overlay and underlay spectrum, the proposed schemes utilize the entire spectrum for underlay transmission to minimize the PU interference while using the spectrum holes for overlay transmission to maximize the data rate. Two techniques that operate at full-load and overload scenarios are proposed. The overload system is then extended to the multiuser underlay case to further improve spectrum utilization.

Design, Modeling, and Performance Analysis of Multi-Antenna Heterogeneous Cellular Networks

This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multiple-input multiple-output (MIMO) heterogeneous cellular networks with linear zero-forcing transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information. The generalized tiers of base stations may differ in terms of their Poisson point process spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access and single-user beamforming transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on the state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input single-output transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments.

Sleep mode mechanisms in dense small cell networks

Data traffic continues to increase exponentially and operators are continuously upgrading their networks to meet this demand. The resulting capital and operational expenditures have limited revenues and the associated energy costs and CO2 emissions have raised economic and ecological concerns. In this paper, we use the stochastic geometry approach to investigate different sleep mode mechanisms that can address both capacity and energy efficiency (EE) objectives in dense small cell networks. We derive a multi-user connectivity model that facilitates the study of sleep mode mechanisms and manages the blocking rate of the network. We formulate an optimization framework that minimizes area power consumption using appropriate constraints. Numerical results show that sleep mode mechanisms enhance the EE of dense small cell networks and that the selection criterion of sleep mode candidate base stations is very important.

Energy Efficiency Optimization With Interference Alignment in Multi-Cell MIMO Interfering Broadcast Channels

Characterizing the fundamental energy efficiency (EE) performance of multiple-input-multiple-output interfering broadcast channels (MIMO-IFBC) is important for the design of green wireless system. In this paper, we propose a new network architecture proposition based on EE maximization for Multi-Cell MIMO-IFBC within the context of interference alignment (IA). Particularly, EE is maximized subject to maximum power and minimum throughput constraints. We propose two schemes to optimize EE for different signal-to-noise ratio (SNR) regions. For high-SNR operating regions, we employ a grouping-based IA scheme to jointly cancel intra- and inter-cell interferences and thus transform the MIMO-IFBC to a single-cell MIMO scenario. A gradient-based power adaptation scheme is proposed based on water-filling power adaptation and singular value decomposition to maximize EE for each cell. For moderate SNR cases, we propose an approach using dirty paper coding (DPC) with the principle of multiple access channel and broadcast channel duality to perform IA while maximizing EE in each cell. The algorithm in its dual form is solved using a subgradient method and a bisection searching scheme. Simulation results demonstrate the superior performance of the proposed schemes over several existing approaches. It also shows that interference-nulling-based IA approaches outperform hybrid DPC-IA approach in high-SNR region, and the opposite occurs in low-SNR region.

Performance based receive antenna selection for V-BLAST systems

Multiple antennas wireless systems can achieve large capacity at the expense of high hardware cost associated with the radio frequency chains. Antenna selection schemes make use of more antennas than RF chains and select a subset of antennas to effectively reduce the hardware cost and power consumption without much capacity loss. In this paper, the problem of receive antenna selection in V-BLAST systems is investigated. Two performance based selection criteria are proposed, namely the min-max MSE and min-first stage MSE criteria. The min-max criterion achieves the best performance at the expense of high computational complexity. Complexity reduced algorithms for this selection scheme are discussed. Analytical proof is provided to show the suboptimality of the capacity based selection to the performance based selection. The hybrid scheme, which combines the performance and capacity based selection approaches is proposed, it provides a good trade-off between performance and complexity. Computer simulations demonstrate that the complexity reduction algorithms and the hybrid scheme perform better and also with a lower complexity than the capacity based selection algorithm under most system configurations. Finally, robustness of the min-max MSE criterion under channel estimation errors is evaluated via computer simulations.

Asynchronous Cooperative Relaying for Vehicle-to-Vehicle Communications

Cooperative diversity exploits the broadcast nature of wireless channels and uses relays to improve link reliability. Most of the cooperative communication protocols are assumed to be synchronous in nature, which is not always possible in vehicle-to-vehicle (V2V) communication due to fast moving nature of the nodes. Also the relay nodes are assumed to be half duplex which in turn reduces the spectral efficiency. In this paper, we propose an asynchronous cooperative communication protocol exploiting polarization diversity, which does not require synchronization at the relay node. Dual polarized antennas are employed at the relay node to achieve full duplex amplify-and-forward (ANF) communication. Hence the transmission duration is reduced which results into an increased throughput rate. Capacity analysis of the proposed scheme ascertains the high data rate as compared to conventional ANF. Bit error rate (BER) simulation also shows that the proposed scheme significantly outperforms both the non-cooperative single-input single-output and the conventional ANF schemes. Considering channel path loss, the proposed scheme consumes less total transmission energy as compared to the conventional ANF and non-cooperative scheme. Thus the proposed scheme is suitable for high rate and energy efficient relay-enabled communication.

Asynchronous Polarized Cooperative MIMO Communication

In cooperative wireless network, the users exploit spatial diversity by cooperating with each other. This alleviates the detrimental effects of fading and offers reliable data transfer. In this paper, we present a novel asynchronous cooperative multi-input multi-output (MIMO) communication scheme in the presence of polarization diversity which does not require synchronization at the relay node. Utilizing dual-polarized antennas, the relay node achieves full duplex amplify-and-forward (ANF) communication. Hence the transmission duration is significantly reduced which in turn results into an increased throughput rate. Capacity analysis of the proposed system ascertains the high data rate as compared to the conventional ANF protocol. Bit error rate simulation also shows that the proposed scheme significantly outperforms both the non-cooperative single-input single-output and the conventional ANF schemes.

Energy allocation for green multiple relay cooperative communication

Cooperative communication achieves diversity through spatially separated cooperating nodes, which are battery powered in most applications. Therefore the energy consumption must be minimized without compromising the quality of service. In this context, we present a novel energy allocation scheme for multiple relay nodes that results in efficient cooperative multiple-input multiple-output (MIMO) communication. Considering channel path loss, the total transmission energy is distributed between the source and the relay nodes. The energy distribution ratio between the relay and direct link is optimized such that the quality of received signal is maintained with minimum total transmission energy consumption. We calculate the energy distribution ratio analytically and verified it through computer simulation. With the new energy allocation scheme, the system also obtains an increased channel capacity as compared to the cooperative scheme with conventional equal energy allocation and the non-cooperative scheme. Optimal relay positioning with the proposed energy allocation scheme is also explored to maximize the capacity.