Network-centric cooperation schemes for uplink interference management in cellular networks

Abstract

The huge growth in demand for wireless data, combined with shortages of spectrum, has led to an urgent need for spectral effi ciency and cell-edge performance improvements in cellular networks. Macrocells are shrinking in size, and heterogeneous networks are being deployed where small cells and macrocells now share the same spectrum. With these trends in cellular network evolution, out-of-sector interference is becoming a major impediment. Impairments due to interference are especially severe on the uplink, where near-far effects are more likely to be experienced. This paper provides a holistic view of the network-centric cooperation schemes that have emerged as strong candidates for uplink interference management in evolving cellular networks (e.g., networks based on 3GPP Long Term Evolution based air-interface technologies and beyond). In particular, we introduce three novel approaches: 1) network multiple input multiple output (MIMO), which carries out joint multi-antenna signal processing across sectors; 2) network interference cancellation engine (NICE) which opportunistically cancels dominant interferers that have already been decoded at neighboring sectors and decreases backhaul overhead by one to two orders of magnitude; and 3) a hybrid approach which combines the strengths of both network MIMO and NICE in an attempt to achieve further spectral effi ciency without incurring huge backhaul overhead. Several considerations of both theoretical and practical signifi cance (overhead, latency) related to these approaches are discussed, and simpler variants that may apply in the context of heterogeneous networks are also considered. Quantitative investigations of these network-centric cooperation schemes in realistic operating environments show that substantial improvement may be achieved in average and cell-edge spectral effi ciency.

Resource Allocation in Heterogeneous Wireless Networks

“…In addition to jointly allocating resources of the small cells, CCI can be managed by allocating almost blank subframes (ABS) [30,31], fractional frequency reuse (FFR) techniques [32,33], and MIMO techniques, such as beamforming and joint decoding [34,35,36,28]. By allocating ABSs, CCI among the small cells cannot be managed as ABSs are allocated by the macrocells to mitigate CCI between the macrocell and Motivations and Thesis Objectives the small cells.…”

Identification of inter-cell uplink interferes based on multi-cell scheduling matrix inversion

“…In this paper, we focus on the case of uplink inter-cell interference. Most works related to uplink intercell interference focus on techniques, such as interference alignment and power control, to be applied once interferers are already identified and ranked by interference strength [4]- [6]. However, up to our knowledge, there is a lack of research on techniques targeting the identification and ranking of users from neighbor cells by level of mean interference power.…”

“…Note that other LSR mappings may require P > 1 to obtain sufficient averaging of fading 4. For comparison, in LTE-Advanced, the reported RSRP can take one of 98 values from −140 dBm to −44 dBm, which also requires 7 bits.…”

Cloud Assisted Resource Management for Hyper-Dense Small Cell Networks

“…In addition to jointly allocating resources of the small cells, CCI can be managed by allocating almost blank subframes (ABS) [3], [4], fractional frequency reuse (FFR) techniques [5], [6], and multiple-input and multiple-output (MIMO) techniques, such as beamforming and joint decoding [1], [7]- [9]. By allocating ABSs, CCI among the small cells cannot be managed as ABSs are allocated by the macrocells to mitigate CCI between macro and small cells.…”