The IEEE 802.11 working group has formed a new Task Group, 802.11bn, to develop a new amendment to support ultra-high reliability (UHR) for Wi-Fi networks, which will eventually shape what Wi-Fi 8 will look like. In this paper, we propose a probabilistic shaping (PS) scheme to improve the spectrum and power efficiency in medium to high signal to noise ratio (SNR) regime forWi-Fi 8. The integration and compatibility with legacy Wi-Fi systems, as well as other Wi-Fi 8 candidate technologies like unequal modulation (UEQM) are addressed. An architecture with a single low-density parity-check (LDPC) encoder and multiple shaping encoders is devised to adapt to different qualities of spatial channels. Furthermore, we propose practical techniques to resolve issues like error propagation, scrambler re-synchronization, and packet length determination to ensure compatibility with legacy scrambling, subframe detection, and packaging flow. It is shown that the proposed constellation shaping scheme provides average 0.89 dB shaping gains over the legacy Wi-Fi scheme, and the shaping gains remain when UEQM and lifted LDPC are applied.

Small-cells in licensed spectrum and unlicensed access via Wi-Fi are two commonly used options to reduce the demand for conventional macro-cellular networks and to provide expanded wireless services to low mobility users. The mix of these technologies depends on both the decisions made by wireless service providers (SPs) that seek to maximize revenue, and the allocation of licensed and unlicensed spectrum by regulators. In this paper, we study these interactions and consider heterogeneous cellular networks together with unlicensed access. Both a single monopoly SP and multiple competing SPs are investigated. The SPs split any available licensed spectrum into two separate bands for macro- and small-cells, which are then used to serve two types of users: mobile and fixed. Mobile users must be served by macro-cells only, whereas fixed users can be served by either macro- or small-cells, or alternatively by unlicensed access service. While the providers charge a (different) price per unit rate for licensed access services (macro- or small-cell), unlicensed access is free. We formulate a sequential game in which the users choose a service that yields the highest payoff, and the providers allocate bandwidth across macro-/small-cells. In general, the competition from unlicensed access results in inefficient (albeit unique) market equilibria, and in many cases all or some SPs allocate no resources to small-cell deployment. We conclude by showing how our framework can also be used to optimize the fraction of unlicensed spectrum when new bandwidth becomes available.

Small-cells deployed in licensed spectrum can expand wireless service to low mobility users, which potentially reduces the demand for macro-cellular networks with wide-area coverage. Introducing such heterogeneity also makes network resource allocation more complicated. To understand these challenges and tradeoffs we present a two-tier heterogeneous wireless network model with two types of users: mobile users that can only connect to macro-cells; and fixed users that can associate with either macro-cells or small-cells. We study pricing strategies and bandwidth allocation across macro- and small-cells, assuming both monopoly and competitive Service Providers (SPs). For a monopoly SP, we characterize the revenue-maximizing prices and bandwidth allocations. We then consider a competitive scenario, and we show the existence of a unique Nash equilibrium. The possible Nash equilibria for different system parameters are sorted into four categories corresponding to whether or not different SPs assign bandwidth to the macro- and/or small-cells. We also study the allocations that maximize social welfare. For the competitive scenario, we characterize the conditions under which the optimal social welfare is obtained in equilibria as the number of SPs tends to infinity. Case study examples and numerical results illustrate the corresponding pricing and bandwidth allocations.

Small cells deployed in licensed spectrum and unlicensed access via WiFi provide different ways of expanding wireless services to low mobility users. That reduces the demand for conventional macro-cellular networks, which are better suited for wide-area mobile coverage. The mix of these technologies seen in practice depends in part on the decisions made by wireless service providers that seek to maximize revenue, and allocations of licensed and unlicensed spectrum by regulators. To understand these interactions we present a model in which a service provider allocates available licensed spectrum across two separate bands, one for macro- and one for small-cells, in order to serve two types of users: mobile and fixed. We assume a service model in which the providers can charge a (different) price per unit rate for each type of service (macro- or small-cell); unlicensed access is free. With this setup we study how the addition of unlicensed spectrum affects prices and the optimal allocation of bandwidth across macro-/small-cells. We also characterize the optimal fraction of unlicensed spectrum when new bandwidth becomes available.

Deployment of LTE in unlicensed bands is being considered in Rel-13 of LTE. This feature is called Licensed-Assisted Access (LAA) using LTE. Unlicensed band is attractive due to the large amount of available spectrum. However, in shared spectrum the coexistence between LAA and WiFi systems becomes a primary challenge. This paper presents an analytical framework to investigate the downlink coexistence performance between two systems with a simple listen-before-talk (LBT) mechanism enforced on LAA. Using this framework, theoretical models based on Markov chains are established for both systems and downlink throughput can be calculated. Numerical results from the models show that the simple listen-before-talk scheme is very effective in LAA and LAA coexistence scenario (i.e. two LAA systems sharing the same spectrum). In LAA and WiFi coexistence scenario, it can improve WiFi performance substantially.

This paper considers a one-dimensional model for a cellular network in which neighboring base stations may cooperatively transmit to users located between them. A distributed algorithm is given for deciding on the power allocation of each base station as well as on which users to serve either cooperatively or individually. The algorithm is proven to converge monotonically and the sum rate performance of different limit points is illustrated. Numerical results are presented that illustrate the performance of the algorithm in terms of sum rate, convergence speed and a fairness metric.