Integer decomposition for polyhedra defined by nearly totally unimodular matrices

We call a matrix $A$ nearly totally unimodular if it can be obtained from a totally unimodular matrix $\tilde{A}$ by adding to each row of $\tilde{A}$ an integer multiple of some fixed row a^{\ssf T} of $\tilde{A}$. For an integer vector $b$ and a nearly totally unimodular matrix $A$, we denote by $P_{A,b}$ the integer hull of the set ${x\in{\Bbb R}^n\mid Ax\leq b}$. We show that $P_{A,b}$ has the integer decomposition property and that we can find a decomposition of a given integer vector $x\in kP_{A,b}$ in polynomial time

Improving the Performance of Medium Access Control Protocols for Mobile Adhoc Network with Smart Antennas

Requirements for high quality links and great demand for high throughput in Wireless LAN especially Mobile Ad-hoc Network has motivated new enhancements and work in Wireless communications such as Smart Antenna Systems. Smart (adaptive) Antennas enable spatial reuse, increase throughput and they increase the communication range because of the increase directivity of the antenna array. These enhancements quantified for the physical layer may not be efficiently utilized, unless the Media Access Control (MAC) layer is designed accordingly. This thesis implements the behaviours of two MAC protocols, ANMAC and MMAC protocols in OPNET simulator. This method is known as the Physical-MAC layer simulation model. The entire physical layer is written in MATLAB, and MATLAB is integrated into OPNET to perform the necessary stochastic physical layer simulations. The aim is to investigate the performance improvement in throughput and delay of the selected MAC Protocols when using Smart Antennas in a mobile environment. Analytical methods were used to analyze the average throughput and delay performance of the selected MAC Protocols with Adaptive Antenna Arrays in MANET when using spatial diversity. Comparison study has been done between the MAC protocols when using Switched beam antenna and when using the proposed scheme. It has been concluded that the throughput and delay performance of the selected protocols have been improved by the use of Adaptive Antenna Arrays. The throughput and delay performance of ANMAC-SW and ANMAC-AA protocols was evaluated in details against regular Omni 802.11 stations. Our results promise significantly enhancement over Omni 802.11, with a throughput of 25% for ANMAC-SW and 90% for ANMC-AA. ANMAC-AA outperforms ANMAC-SW protocol by 60%. Simulation experiments indicate that by using the proposed scheme with 4 Adaptive Antenna Array per a node, the average throughput in the network can be improved up to 2 to 2.5 times over that obtained by using Switched beam Antennas. The proposed scheme improves the performances of both ANMAC and MMAC protocols but ANMAC outperforms MMAC by 30%

End-to-End Simulation of 5G mmWave Networks

Due to its potential for multi-gigabit and low latency wireless links, millimeter wave (mmWave) technology is expected to play a central role in 5th generation cellular systems. While there has been considerable progress in understanding the mmWave physical layer, innovations will be required at all layers of the protocol stack, in both the access and the core network. Discrete-event network simulation is essential for end-to-end, cross-layer research and development. This paper provides a tutorial on a recently developed full-stack mmWave module integrated into the widely used open-source ns--3 simulator. The module includes a number of detailed statistical channel models as well as the ability to incorporate real measurements or ray-tracing data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and highly customizable, making it easy to integrate algorithms or compare Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example. The module is interfaced with the core network of the ns--3 Long Term Evolution (LTE) module for full-stack simulations of end-to-end connectivity, and advanced architectural features, such as dual-connectivity, are also available. To facilitate the understanding of the module, and verify its correct functioning, we provide several examples that show the performance of the custom mmWave stack as well as custom congestion control algorithms designed specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and Tutorials (revised Jan. 2018

Joint QoS-Aware Scheduling and Precoding for Massive MIMO Systems via Deep Reinforcement Learning

The rapid development of mobile networks proliferates the demands of high data rate, low latency, and high-reliability applications for the fifth-generation (5G) and beyond (B5G) mobile networks. Concurrently, the massive multiple-input-multiple-output (MIMO) technology is essential to realize the vision and requires coordination with resource management functions for high user experiences. Though conventional cross-layer adaptation algorithms have been developed to schedule and allocate network resources, the complexity of resulting rules is high with diverse quality of service (QoS) requirements and B5G features. In this work, we consider a joint user scheduling, antenna allocation, and precoding problem in a massive MIMO system. Instead of directly assigning resources, such as the number of antennas, the allocation process is transformed into a deep reinforcement learning (DRL) based dynamic algorithm selection problem for efficient Markov decision process (MDP) modeling and policy training. Specifically, the proposed utility function integrates QoS requirements and constraints toward a long-term system-wide objective that matches the MDP return. The componentized action structure with action embedding further incorporates the resource management process into the model. Simulations show 7.2% and 12.5% more satisfied users against static algorithm selection and related works under demanding scenarios

Routing and Broadcast Development for Minimizing Transmission Interruption in Multi rate Wireless Mesh Networks using Directional Antennas

Using directional antennas to reduce interference and improve throughput in multi hop wireless networks has attracted much attention from the research community in recent years. In this paper, we consider the issue of minimum delay broadcast in multi rate wireless mesh networks using directional antennas. We are given a set of mesh routers equipped with directional antennas, one of which is the gateway node and the source of the broadcast. Our objective is to minimize the total transmission delay for all the other nodes to receive a broadcast packet from the source, by determining the set of relay nodes and computing the number and orientations of beams formed by each relay node. We propose a heuristic solution with two steps. Firstly, we construct a broadcast routing tree by defining a new routing metric to select the relay nodes and compute the optimal antenna beams for each relay node. Then, we use a greedy method to make scheduling of concurrent transmissions without causing beam interference. Extensive simulations have demonstrated that our proposed method can reduce the broadcast delay significantly compared with the methods using omnidirectional antennas and single-rate transmission. In addition, the results also show that our method performs better than the method with fixed antenna beams. Keywords: Multihop, Wireless, Mesh, Omnidirectional