This letter considers a network where nodes share a wireless channel to work in turn as pulse radars for target detection and as transmitters for data exchange. Radar detection range and network throughput are studied using stochastic geometry tools. We derive closed-form expressions that identify the key tradeoffs between radar and communication operations. Results reveal interesting design hints, and stress a marked sensitivity of radar detection to communication interference.

This paper describes a new tool aimed for rapid development and modeling of MAC protocols that is based on hierarchical finite state machines with concurrency models. The developed tool is named Decomposite MAC Description Language (DMDL) and we arc going to provide it open source in order to support MAC protocol design, implementation, and exchange of ideas among researchers. Following the modular design philosophy, the atomic elements of DMDL are the elementary MAC function components selected from a large-scale survey on different types of MAC that we have conducted. In DMDL, a MAC protocols is modeled as a directed graph with the MAC function components at the vertices. A token-like controlling unit is defined to pass control signals and data elements among MAC function components via the directed connections. The high decomposability and modularity enables DMDL to be used as a pure graphical language, and the concurrency nature of the synchronous data flow inherently ensures concurrency as a fundamental feature of DMDL. However, the tool supports also low level direct programmability and mixing of different programming languages through a common GNU Radio approach. In order to expands its usability, DMDL is developed on GNU Radio with a number of classic MAC protocols. The performance of the protocols implemented with DMDL is in accordance with the theoretical expectations, which demonstrates that DMDL is an efficient MAC designing and implementing tool with high flexibility and reusability.

In millimeter-wave wireless networks, the use of narrow beams, required to compensate for the severe path-loss, complicates the cell-discovery and initial access. In this paper, we investigate the feasibility of random beam forming and enhanced exhaustive search for cell-discovery by analyzing the latency and detection failure probability in the control-plane and the user throughput in the data-plane. We show that, under realistic propagation model and antenna patterns, both approaches are suitable for 3GPP New Radio cellular networks. The performance gain, compared to the heavily used exhaustive and iterative search schemes, is more prominent in dense networks and large antenna regimes and can be further improved by optimizing the beam forming code-books.

QUIC is a new transport layer protocol proposed by Google that is rapidly increasing its share from Internet traffic. It is designed to improve performance for HTTPS connections and partly replace TCP, the dominant standard of Internet for decades, in application scenarios where new requirements such as packet encryption, stream multiplexing and connection migration are emerging and which have proven to be challenging for the TCP service model. QUIC has been massively deployed to serve some of the most popular Internet services, including YouTube. To enable easy deployment and rapid evolution to the protocol, the current deployment of QUIC runs in user-space, usually as part of the Chrome/Chromium browser. This potentially reduces the achievable performance of the protocol, as each message, including control messages, triggers a context switch between kernel and user spaces. To investigate the potential performance of QUIC in kernel mode and to achieve a fair comparison between QUIC and TCP, we implement QUIC in the Linux kernel where TCP and other transport layer protocols are running. We have conducted extensive measurements in both virtual machines and in a custom-built WIFI testbed to compare the two protocols. The empirical results indicate that QUIC outperforms TCP in major application scenarios such as network with low latency and high packet loss rate, while QUIC also shows a TCP-friendly rate control when the two protocols are running concurrently.

In this paper, we present an analytical model for performance analysis of dynamic proportional fair scheduling (PFS) in downlink power-domain non-orthogonal multiple access (PD-NOMA) networks. In order to develop a tractable model of analytical performance, we relax the condition in the PFS optimization problem and assume an ideal NOMA system with an arbitrary number of multiplexed users per frame. We derive a closed-form solution of the optimal power allocation for the relaxed problem and design a low-complexity algorithm for joint power allocation and user set selection. With this optimal solution, the transmission performance in the ideal NOMA system is proved to be an upper bound. Based on our derivation, we develop an analytical model of the upper bound throughput performance. The analytical performance is used to estimate user data rates and overall throughput in practical NOMA systems. We conduct system-level simulations to evaluate the accuracy of our data rate estimation. The simulation results verify our analysis of the upper bound performance of PFS in NOMA systems and confirm that using its analytical results for data rate estimation guarantees high accuracy. The impact of partial and imperfect channel state information on the estimation performance is investigated as well.

Millimeter-wave (mmWave) networks rely on directional transmissions, in both control plane and data plane, to overcome severe path-loss. Nevertheless, the use of narrow beams complicates the initial cell-search procedure where we lack sufficient information for beamforming. In this paper, we investigate the feasibility of random beamforming for cell-search. We develop a stochastic geometry framework to analyze the performance in terms of failure probability and expected latency of cell-search. Meanwhile, we compare our results with the naive, but heavily used, exhaustive search scheme. Numerical results show that, for a given discovery failure probability, random beamforming can substantially reduce the latency of exhaustive search, especially in dense networks. Our work demonstrates that developing complex cell-discovery algorithms may be unnecessary in dense mmWave networks and thus shed new lights on mmWave system design.

This letter characterizes the effect of mutual interference in a planar network of pulsed-radar devices. Using stochastic geometry tools and the strongest interferer approximation, we derive simple closed-form expressions that pinpoint the role played by key system parameters on radar detection range and false alarm rate. The fundamental tradeoffs of the system between radar performance, network density, and antenna directivity are captured for different path-loss exponents in the no-fading and Rayleigh-fading cases. The discussion highlights practical design hints for tuning the radar parameters. The accuracy of the model is verified through network simulations.

Emerging Wi-Fi technologies are expected to cope with large amounts of traffic in dense networks. Consequently, proposals for the future IEEE 802.11ax Wi-Fi amendment include sensing threshold and transmit power adaptation, in order to improve spatial reuse. However, it is not yet understood to which extent such adaptive approaches - and which variant - would achieve a better balance between spatial reuse and the level of interference, in order to improve the network performance. Moreover, it is not clear how legacy Wi-Fi devices would be affected by new-generation Wi-Fi implementing these adaptive design parameters. In this paper we present a thorough comparative study in ns-3 for four major proposed adaptation algorithms and we compare their performance against legacy non-adaptive Wi-Fi. Additionally, we consider mixed populations where both legacy non-adaptive and new-generation adaptive populations coexist. We assume a dense indoor residential deployment and different numbers of available channels in the 5 Wiz band, relevant for future IEEE 802.11ax. Our results show that for the dense scenarios considered, the algorithms do not significantly improve the overall network performance compared to the legacy baseline, as they increase the throughput of some nodes, while decreasing the throughput of others. For mixed populations in dense deployments, adaptation algorithms that improve the performance of new-generation nodes degrade the performance of legacy nodes and vice versa. This suggests that to support Wi-Fi evolution for dense deployments and consistently increase the throughput throughout the network, more sophisticated algorithms are needed, e.g. considering combinations of input parameters in current variants.

In its evolution to provide ever higher data rates, the Wi-Fi standard has incorporated sophisticated PHY-layer techniques, which has in turn increased the complexity of network-wide interference relationships. Proper modelling of the resulting inter-device interactions is crucial for accurately estimating Wi-Fi network performance, especially in the contemporary context of traffic and network densification. Event-driven simulators like the open-source ns-3 are in principle able to capture these interactions, however it is imperative to validate, against experimental results, whether their underlying models reflect the network behaviour in practice. In this paper we first perform experiments in a large-scale indoor testbed to validate the IEEE 802.11ac Wi-Fi model in ns-3, for various channel width and allocation configurations. Our results show that ns-3 captures Wi-Fi co-channel interactions with reasonable precision, but fails to model adjacent channel interference (ACI), which our experiments show to be critical in dense networks. We therefore propose and implement an ACI model in ns-3. Importantly, our model successfully captures the qualitative behaviour of the CSMA/CA mechanism when transmissions on adjacent channels occur. Further, our ACI implementation significantly improves the accuracy of both the network and per-device throughput estimates for the considered dense IEEE 802.11ac network compared to the basic ns-3 Wi-Fi model without ACI. For example, without ACI modelling, ns-3 overestimates the aggregate network throughput by up to 230%, whereas with our ACI implementation the aggregate throughput estimate is no more than 65% higher than the experimental results.