Howard H. Yang

Heterogeneous Cellular Network With Energy Harvesting-Based D2D Communication

The concept of mobile user equipment (UE) relay (UER) has been introduced to support device-to-device (D2D) communications for enhancing communication reliability. However, as the UER needs to use its own power for other UEs data transmission, relaying information in D2D communication may be undesirable for the UER. To overcome this issue, motivated by the recent advances in energy harvesting (EH) techniques, we propose a D2D communication provided EH heterogeneous cellular network (D2D-EHHN), where UERs harvest energy from an access point (AP) and use the harvested energy for D2D communication. We develop a framework for the design and analysis of D2D-EHHN by introducing the EH region (EHR) and modeling the status of harvested energy using Markov chain. The UER distribution is derived, and a transmission mode selection scheme including the efficient UER selection method is proposed. The network outage probability is derived in close form to measure the performance of D2D-EHHN. Based on our analysis results, we explore the effects of network parameters on the outage probability and the optimal offloading bias in terms of the outage probability. Particularly, we show that having a high EH efficiency enhances the performance of D2D-EHHN, but can also degrade, especially for dense network.

Energy-Efficient Design of MIMO Heterogeneous Networks With Wireless Backhaul

As future networks aim to meet the ever-increasing requirements of high-data rate applications, dense, and heterogeneous networks (HetNets) will be deployed to provide better coverage and throughput. Besides the important implications for energy consumption, the trend toward densification calls for more and more wireless links to forward a massive backhaul traffic into the core network. It is critically important to take into account the presence of a wireless backhaul for the energy-efficient design of HetNets. In this paper, we provide a general framework to analyze the energy efficiency of a two-tier MIMO heterogeneous network with wireless backhaul in the presence of both uplink and downlink transmissions. We find that under spatial multiplexing the energy efficiency of a HetNet is sensitive to the network load, and it should be taken into account when controlling the number of users served by each base station. We show that a two-tier HetNet with wireless backhaul can be significantly more energy efficient than a one-tier cellular network. However, this requires the bandwidth division between radio access links and wireless backhaul to be optimally designed according to the load conditions.

Green device-to-device communication with harvesting energy in cellular networks

The concept of mobile user equipment (UE) relay (UER) has been introduced to support the relaying transmission using device-to-device (D2D) communications for enhancing communication reliability. However, as the UER needs to use its own power for the other UEs data transmission, the D2D communication can be unfair to the UER. To overcome this issue, motivated by the recent advance in energy harvesting (EH) techniques, we consider the D2D communication provided EH cellular network (D2D-EHCN) where the UERs harvest RF energy from a base station (BS) and use the harvested energy for D2D communications. We first derive the UER distribution by taking into account the EH parameters, and propose the transmission mode selection scheme including the UER selection method. After deriving the outage probability of the D2D-EHCN, we explore the effects of the network parameters on the outage probability. Particularly, we show that the outage probability of D2D-EHCN is smaller than that of the cellular network without D2D communication, and their difference becomes more significant when the density of BSs is small.

Opportunistic D2D communication in energy harvesting heterogeneous cellular network

Mobile user equipment relay (UER) has been introduced by 3GPP to enhance communication reliability through device-to-device (D2D) communications. However, as UER needs to use its own power to forward other users data, D2D communication may be unreasonable to the UER. To overcome this issue, motivated by the recent progress in energy harvesting (EH) techniques, we propose a D2D communication provided EH heterogeneous cellular network (D2D-EHHN), where UERs harvest energy from an access point (AP) and use the harvested energy for D2D communication. We first derive the UER distribution according to the EH parameters, and then propose opportunistic D2D communication scheme to determine the transmission mode based on the best UER location. We then explore the effect of network parameters on the outage probability. Particularly, we show that having a high EH efficiency at user equipments (UEs) does not always improve the performance of D2D-EHHN, especially for dense network, and also how EH parameters affect the optimal offloading bias that minimizes the outage probability of D2D-EHHN.

Packet Throughput Analysis of Static and Dynamic TDD in Small Cell Networks

We develop an analytical framework for the performance comparison of small cell networks operating under static time division duplexing (S-TDD) and dynamic TDD (D-TDD). By leveraging stochastic geometry and queuing theory, we derive closed-form expressions for the uplink (UL) and downlink (DL) packet throughput, also capturing the impact of random traffic arrivals and packet retransmissions. Through our analysis, we confirm that: 1) the number of scheduled user equipment may strongly affect the network throughput and 2) D-TDD outperforms S-TDD in DL, with the vice versa occurring in UL, since asymmetric transmissions reduce DL interference at the expense of an increased UL interference. We also find that in asymmetric scenarios, where most of the traffic is in DL, D-TDD provides a DL packet throughput gain by better controlling the queuing delay, and that such gain vanishes in the light-traffic regime.

MIMO HetNets with wireless backhaul: An energy-efficient design

Dense and heterogeneous networks (HetNets) are being deployed to provide better coverage and throughput, thus improving the quality of experience at mobile users. Besides the important implications for energy consumption, the trend towards densification calls for more and more wireless links to forward a massive backhaul traffic into the core network. It is critically important to take into account the presence of a wireless backhaul for the energy-efficient design of HetNets. In this paper, we provide a general framework to analyze the energy efficiency of a two-tier MIMO heterogeneous network with wireless backhaul under spatial multiplexing and dynamic time division duplex. We find that a two-tier HetNet with wireless backhaul can be significantly more energy efficient than a one-tier cellular network. However, this requires the backhaul bandwidth to be carefully allocated according to the network load conditions.

Rate analysis of spatial multiplexing in MIMO heterogeneous networks with wireless backhaul

In this paper, we develop a general framework to analyze the rate performance of a two-tier MIMO heterogeneous network (HetNet) with wireless backhaul under spatial multiplexing. We consider linear precoding and receive filtering in the presence of interference from uplink and downlink transmissions. We find that the sum rate per area of the HetNet is sensitive to the network load, i.e., the number of users served by each base station. We show that a two-tier HetNet with wireless backhaul can achieve higher sum rate per area than a one-tier cellular network. However, this requires the bandwidth division between radio access links and wireless backhaul to be optimally designed according to the load conditions.

Capacity bounds on energy harvesting binary symmetric channels with finite battery

We investigate the capacity of energy harvesting binary symmetric channels with deterministic energy arrival process and finite battery size. Using an abstraction of the physical layer, binary symbols are transmitted. A cost function is associated with each transmitted symbol. Upper and lower bounds on the channel capacity are derived as functions of the normalized exponent of the cardinality of the set of feasible input sequences. Upper and lower bounds on the normalized exponent are established by studying supersets defined by relaxed constraints and employing a harvest-and-transmit signaling scheme, respectively. Numerical results validate that bounds on the exponent imply effective bounds on the channel capacity.

Heterogeneous Cellular Networks With LoS and NLoS Transmissions—The Role of Massive MIMO and Small Cells

We develop a framework for downlink heterogeneous cellular networks with line-of-sight (LoS) and non-LoS transmissions. Using stochastic geometry, we derive tight approximation of average downlink rate that enables us to compare the performance between densifying small cells and expanding base station (BS) antenna arrays. Interestingly, we find that adding small cells into the network improves the downlink rate much faster than expanding antenna arrays at the macro BS. However, when the small cell density exceeds a critical threshold, the spatial densification will lose its benefits and further impair the network capacity. To this end, we provide the optimal small cell density that maximizes the rate via numerical results for practical deployment guidance. In contrast, expanding macro BS antenna array can always benefit the capacity until an upper bound caused by pilot contamination, and this bound also surpasses the peak rate obtained from the deployment of small cells. Furthermore, we find that allocating part of antennas to distributed small cell BSs works better than centralizing all antennas at the macro BS, and the optimal allocation proportion is also given numerically for practical configuration reference. In summary, this paper provides a further understanding on how to leverage small cells and massive MIMO in future heterogeneous cellular networks deployment.

Massive MIMO for Interference Suppression: Cell-Edge Aware Zero Forcing

Ubiquitous high-speed coverage and seamless user experience are among the main targets of next generation wireless systems, and large antenna arrays have been identified as a technology candidate to achieve them. By exploiting the excess spatial degree of freedom from the large number of base station (BS) antennas, we propose a new scheme termed cell-edge-aware (CEA) zero forcing (ZF) precoder for coordinated beamforming in massive MIMO cellular network, which suppresses inter-cell interference at the most vulnerable user equipments (UEs). In this work, we combine the tools from random matrix theory and stochastic geometry to develop a framework that enables us to quantify the performance of CEA-ZF and compare that with a conventional cell-edge-unaware (CEU) ZF precoder in a network of random topology. Our analysis and simulations show that the proposed CEA-ZF precoder outperforms CEU-ZF precoding in terms of (i) increased aggregate per-cell data rate, (ii) higher coverage probability, and (iii) significantly larger \(95\,\%\)-likely rate, the latter being the worst data rate that a UE can reasonably expect to receive when in range of the network. Results from our framework also reveal the importance of scheduling the optimal number of UEs per BS, and confirm the necessity to control the amount of pilot contamination received during the channel estimation phase.