Suresh Kalyanasundaram

Dynamic point selection for LTE-advanced: Algorithms and performance

Dynamic Point selection (DPS) is a key Downlink (DL) Coordinated Multipoint (CoMP) technique that switches the serving data Transmission Point (TP) of a User Equipment (UE) dynamically among the UEs cooperating set of TPs without requiring a cell handover. It provides performance improvement due to TP selection-diversity gains and dynamic UE load balancing benefit. In this paper, we propose two simple DPS schemes that take into account the UEs current channel conditions and the cell loading conditions to make the UEs TP switching decisions. We show that these schemes improve the system performance under different practical and realistic settings, such as, cell handover margin, TP switching periods, bursty traffic conditions, and cooperation cell cluster sizes.

Performance Analysis of Centralized RAN Deployment with Non-Ideal Fronthaul in LTE-Advanced Networks

Centralized RAN and baseband pooling architectures are increasingly being seen as the way cellular technologies will be deployed in the future due to a number of advantages they provide to the operator. However, LTE and LTE-Advanced were designed with a distributed architecture in mind. Therefore, there are certain inherent technical issues when the link connecting the baseband and RRU (Remote Radio Unit) has a non-negligible latency. In this paper, we study the impact of this non-ideal fronthaul on the downlink and uplink performance of LTE-Advanced networks. We show that, while the impact on the peak throughput is quite severe, it is more modest when we have a larger number of active UEs. The degradation in performance is larger in the uplink than in the downlink due to the synchronous HARQ mechanism used in LTE uplink. In the downlink, we compare the performance of centralized RAN with that of distributed RAN in case of non-ideal fronthaul (FH) and backhaul (BH), respectively, and determine whether it is better to incur backhaul or fronthaul latency from a performance perspective. In the uplink, we analyze the loss in performance due to fronthaul latency. We have developed a novel look-ahead scheduling scheme that results in significant improvement in performance, especially when the number of active UEs is small.

Optimal power allocation and user selection in non-orthogonal multiple access systems

In this paper, we focus on the design of an optimal power allocation algorithm and an efficient user selection scheme for the downlink of a non-orthogonal multiple access (NOMA) system with power-domain user multiplexing at the transmitter side and successive interference cancellation (SIC) on the receiver side. We have derived an optimal power allocation solution in closed-form with the objective of maximizing the weighted sum rate subject to a maximum power constraint. The optimization problem is solved using the Karush-Kuhn-Tucker (KKT) conditions. A greedy user selection algorithm is used to schedule the best set of multiplexed users satisfying the criterion of maximizing sum proportional fairness (PF) metric. Systemlevel simulation results are provided to assess and compare the performance gains of the proposed algorithm in terms of important key system performance indicators.

Interference Penalty Algorithm (IPA) for inter-cell interference co-ordination in LTE uplink

In this paper, we develop a novel inter-cell interference co-ordination scheme that takes into account the interference cost on neighboring cells. We formulate a multi-cell utility maximization problem and subsequently decouple it into single-cell optimization problems by including an interference penalty. By solving this decoupled problem, we derive policies for user selection, resource allocation, and power-control. Since the coupling between cells is indirectly taken into account by means of the users channel gain to the neighboring cells, our simulation results show that this distributed solution has no degradation in performance while little or no inter-cell co-ordination is required. We present simulation results that show that the Interference Penalty Algorithm (IPA) provides significant improvement in sector and cell-edge throughputs.

Performance Analysis of Interference Penalty Algorithm for LTE Uplink in Heterogeneous Networks

Heterogeneous networks (Hetnets) introduce an imbalance between downlink and uplink because the downlink transmit powers of the macro and pico eNodeBs can differ by as much as 16 dB. However, the user equipment (UE)s maximum uplink transmit power is the same regardless of whether the UE is connected to the macro or the pico eNodeB. The uplink throughput performance depends both on the SINR that the UEs see and the number of PRBs that each UE can get allocated. Due to the difference in the transmit powers of the eNodeBs, the number of UEs that attach to the pico eNodeB is typically smaller than the number that attach to the macro eNodeB. In this work, we consider these impacts and optimize the power control settings of the macro and pico UEs so that the cell-edge and average UE throughput are improved. We study the performance under two different power control schemes: Fractional Power Control (FPC) and Interference Penalty Algorithm (IPA). Using simulations, we study the impact of various parameter settings on the performance of IPA. Based on our studies, we can conclude that the macro UEs transmit power needs to be larger than that of the pico UE to overcome the larger number of UEs attaching to the macro eNodeB. We also study the impact of imperfect knowledge of neighbor cell path losses on the uplink performance of IPA.

Resource allocation for self-backhauled networks with half-duplex small cells

Large-scale ad-hoc deployment of small cells or access points is expected to improve the coverage and spectrum reuse. The need for high-cost optical fiber or similar wired connectivity for backhaul can be mitigated by using radio access spectrum for backhaul links. The radio resources are shared among access links and self-backhaul links. This is referred as in-band self-backhauling. In this paper, we propose a solution for the scheduling, resource allocation and flow control problem for networks with self-backhauled half-duplex small cells. We formulate the resource allocation and scheduling problem as an optimization problem, where the objective is to maximize the sum-utility. The logarithm of user equipment (UE) throughputs is used as the utility function. The optimization problem is solved using Karush-Kuhn-Tucker (KKT) conditions. The solution obtained is used to develop a distributed method where the small cells pass on the most parsimonious information to the macro cell to aid it in its scheduling. Based on the intuition from the optimal long-term fraction of resources to be allocated, we propose a solution for the transmission time interval (TTI)-level scheduling problem. Further, we propose a flow-control algorithm between the macro eNodeB (eNB) and the small cell UEs that determines which small cell UEs data needs to be transmitted based on an appropriate feedback on the UE buffer status from the small cell. System-level simulation results are provided to quantify the performance gains of the proposed algorithms for full buffer traffic under different scenarios.