Performance Impact of LoS and NLoS Transmissions in Dense Cellular Networks (1503.04251v3)

Abstract: In this paper, we introduce a sophisticated path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to study their impact on the performance of dense small cell networks (SCNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE), assuming both a general path loss model and a special case with a linear LoS probability function. The performance impact of LoS and NLoS transmissions in dense SCNs in terms of the coverage probability and the ASE is significant, both quantitatively and qualitatively, compared with the previous work that does not differentiate LoS and NLoS transmissions. Our analysis demonstrates that the network coverage probability first increases with the increase of the base station (BS) density, and then decreases as the SCN becomes denser. This decrease further makes the ASE suffer from a slow growth or even a decrease with network densification. The ASE will grow almost linearly as the BS density goes ultra dense. For practical regime of the BS density, the performance results derived from our analysis are distinctively different from previous results, and thus shed new insights on the design and deployment of future dense SCNs.

• The paper presents an advanced analytical framework using stochastic geometry to derive closed-form expressions for coverage probability and ASE considering LoS and NLoS transmissions.
• It finds that increasing base station density initially improves coverage but eventually leads to higher interference, reducing overall performance.
• The study reveals a non-linear ASE trend with sublinear growth at specific densities, underscoring the need for careful network densification in future 5G deployments.

Performance Impact of LoS and NLoS Transmissions in Dense Cellular Networks

The paper at hand explores evaluating the implications of differentiating between Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) transmissions on the performance of dense small cell networks (SCNs). The investigation is grounded in a sophisticated path loss model that integrates both LoS and NLoS paths to analytically address the coverage probability and area spectral efficiency (ASE) of SCNs. This approach represents a significant shift from prior analyses prevalent in the literature, which typically employ oversimplified path loss models without distinguishing between LoS and NLoS transmissions.

Analytical Framework

The authors leverage stochastic geometry to model the positions of base stations (BSs) in the network as a Homogeneous Poisson Point Process (HPPP). This facilitates tractable analysis of essential performance metrics: coverage probability, the likelihood that a user's signal-to-interference-plus-noise ratio (SINR) exceeds a threshold, and ASE, the system's spatial spectral efficiency. They derive closed-form expressions for these metrics using a general path loss model that accommodates both LoS and NLoS variations and evaluate them under specific, 3GPP-compliant scenarios. Notably, the paper explores the network's performance when the LoS probability function is linear, a step forward in aligning theoretical models with practical deployment scenarios advised by industry standards.

Key Findings

• Coverage Probability Dynamics: The analysis reveals a non-trivial relationship between BS density and coverage probability. As BS density increases initially, coverage improves due to reduced path loss. However, when BS density surpasses a certain threshold, increased interference from nearby BSs begins to dominate, thus reducing coverage probability. This finding is pivotal, as it challenges the perception that increased density unilaterally enhances network performance.
• ASE Trends: The ASE exhibits a non-linear growth pattern, with potential sublinear growth or even decline when the network reaches certain densities. This is attributed to a rapid shift from NLoS to LoS conditions in dense deployments, which impacts interference and network dynamics. The paper notes that, eventually, ASE resumes a near-linear increase at ultra-high densities, indicating stabilization of interference effects.

Implications and Future Directions

The insights derived from differentiating LoS and NLoS paths suggest substantial implications for the design and deployment of future dense cellular networks, such as 5G. The recognition that ASE performance may suffer when BS density is within specific ranges is critical for network planning, particularly for operators transitioning from 4G to 5G. It underscores the importance of careful planning in network densification strategies to avoid undesirable performance troughs.

In extending this work, future research could explore more complex stochastic models, incorporate advanced propagation phenomena like Rician fading, or consider the impacts of emerging interference mitigation techniques in ultra-dense scenarios. Additionally, the exploration of directional antennas or hybrid deployments with heterogeneous elements to optimize LoS conditions might provide further valuable insights.

In summary, the paper presents a robust analytical framework addressing significant real-world phenomena that were previously oversimplified. The findings contribute to a nuanced understanding of SCN performance and offer a foundation for advancing network deployment strategies considering both LoS and NLoS transmission characteristics.