IEEE 802.11 medium access control enhancements based on simultaneous multiple‐input multiple‐output bandwidth sharing

This chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance.

A joint MIMO-OFDM transceiver and MAC design for mobile ad hoc networking

Multiple input multiple output (MIMO) technology has evolved over the past few years into a technology with great potential to drive the direction of future wireless communications. MIMO technology has become a solid reality when massive MIMO systems (MIMO with large number of antennas and transceivers) were commercially deployed in several countries across the world in the recent past. Moreover, MIMO has been integrated into state-of-the-art paradigms such as fifth-generation (5G) networks as one of the main enabling technologies. MIMO possesses many attractive and highly desirable properties such as spatial multiplexing, diversity gains, and adaptive beamforming gains that leads to high data rates, enhanced reliability, and other enhancements. Nevertheless, beyond 5G technologies demand wireless communication systems with, among other properties, immensely higher data rates and better reliability simultaneously at the same time. In this work, a new, novel MIMO technique for simultaneously achieving multiplexing and diversity gains as well as completely eliminating any processing at the MIMO receiver, leading to advantages such as low complexity and low power consumption, is proposed. The proposed technique employs the design of interference-canceling matrices, which are calculated from the channels between the transceiver antennas, where the matrices are employed at the base station to help achieve multiplexing and diversity gains simultaneously. The novelty and efficiency of the introduced paradigm is demonstrated via mathematical models and validated by Monte Carlo simulations. Results indicate that the proposed system outperforms conventional MIMO models.

Multiple-Input Multiple-Output (MIMO) technologies utilize multiple antennas at the transceivers and enable enhanced diversity or multiplexing gain. The first implementations of MIMO technology appeared in cellular communication and Wi-Fi systems. One of the main problems with early MIMO systems is their limited performance in meeting the requirements of next generation communication systems. Specifically, the parameters like peak data rates, spectrum efficiency and energy efficiency constraints cannot be met with existing MIMO architectures. Hence, early MIMO techniques evolved to massive MIMO (mMIMO) type of communication as the number of antennas at both transmitters and receivers increased. Included in 5G New Radio standard, mMIMO enabled an increase the spectral efficiency and coverage compared with earlier MIMO techniques. Nowadays, there exists an ever-increasing interest in the application of advanced MIMO technologies in 6G networks. These applications include ultra massive MIMO (mMIMO), holographic MIMO and intelligent reflecting surface (IRS) assisted MIMO. These new advanced MIMO techniques either employ larger number of antennas or extremely large aperture arrays compared with mMIMO and are named as extremely large-scale MIMO. This paper presents a detailed overview of all these techniques. Joint design of wireless communication and radar sensing, named as integrated sensing and communication (ISAC) as well, has shown to improve spectrum efficiency and reduce power consumption. Recent novel research on ISAC exploits the application of MIMO technology specifically in joint communication and radar sensing (JCS) systems. In this aspect, the other objective of this work is to exploit MIMO communication and MIMO radar coexistence. After summarizing the current state of the art on MIMO radar systems, this paper exploits joint application of advanced MIMO communication and radar sensing. Finally, it aims to offer a perspective on future research directions and the potential of overall MIMO systems discussed in the paper.

In this paper we propose a simple relay enabled medium access (SRMAC) protocol that enables cooperative relay transmissions. Due to the wireless signal power attenuation with distance, using a relay in a wireless network can make wireless networking more bandwidth efficient at the expense of requiring multiple transmissions for a single packet. Standard MAC protocols such as the IEEE 802.11 MAC protocol, while useable with relaying, however are not designed explicitly for relay communication. When IEEE 802.11 MAC protocol is used for cooperative communication such a relaying, each packet transmission would need to separately contend for the channel via a channel access procedure which can use significant resources (both energy and bandwidth). Because using a single relay requires two transmissions, an efficient medium access control (MAC) protocol that supports two hop transmission is needed. We introduce a protocol, SRMAC, which is a simple cooperative MAC protocol that utilizes information from the physical layer for the MAC operation of relay networks. We consider the bandwidth efficiency of SRMAC protocol considering both the physical layer and MAC layer. The SRMAC protocol includes the possibility of both cooperative transmission and direct transmission. With SRMAC, cooperative transmission (relaying) can be dynamically chosen when it is more beneficial than direct transmission. The SRMAC protocol can improve the throughput by up to 20% compared to conventional MAC protocols.

In this paper, we propose a detailed energy survey of the physical, data link, and network layer by analytical techniques. We also show the impact of regular sleep periods on node energy consumption and present a comparison analysis of single-hop vs. multi-hop communications in the energy realm. A detailed energy expenditure analysis of not only the physical layer but also the link and network layer provides a basis for developing new energy efficient wireless sensor networks. Regular, coordinated sleeping extends the lifetime of sensor nodes, but systems can only benefit from sleeping in terms of transmitted packets if the data arrival rate to the system is low. Energy efficiency is the driving motivation for it can be considered the most important factor for wireless sensor networks because of the power constraints set by battery operation. Radio solutions in the lower ISM bands are attractive because of their relatively easy implementation and low power consumption. However, the data rates of these commercial radios are also relatively low, limiting transmittable frame sizes to a few tens of octets along with strict duty cycle requirements. From the analysis we extract key parameters of selected MAC protocols and show that some traditional mechanisms, such as binary exponential backoff, have some inherent problems. We also argue that single-hop communications has up todo% lower energy consumption than multi-hop forwarding within the feasible transmission distances of an ISM radio. Index Terms-Energy efficiency, Wireless sensor net- works, Medium access control (MAC) protocols, multi-hop communications a duty cycIe (Z), (3), which is normally 10% for the 434MHz band and 1% for the 868MHz band. The duty cycle is defined as the ratio, expressed as a percentage, of the maximum transmitter on-time, relative to a one hour period. When a sensor network is expected to work continuously, this duty cycle has to be taken into account and it can affect the energy efficiency of a network. In this paper we perform cross-layer analysis by pre- senting topology, medium access control (MAC) and ra- dio transceiver energy consumption models that work in unison. The hear topology model represents a common network after network layer route discovery has been accomplished. We use an energy consumption model for the transmission and reception of MAC frames originally presented in (4), develop a coordinated sleep group energy consumption model, and analytically investigate the effect of sleep on sensor networks using three MAC protocols. From the analysis we show that although in an ideal scenario multi-hop communications perform better than single-hop communications, realistic energy models and especially the MAC protocol design have a significant impact. We propose a multi-group sleep model for our nanoMAC protocol, and show that reg- ular sleep periods have a significant, energy reducing impact on node energy consumption with low traf!fic rates. The radio transceiver energy model takes into account several important radio parameters and we use the RFM TRlOOO and RFM radio designers guide (5) for realistic transceiver parameters. The main metric used is absolute energy, consumption per useful transmitted bit. This means only the MAC or thc network protocol data unit (PDU) will be considered and all the other communicated bits, headers, control frames, preambles, etc. are considered as overhead. The rest of the paper is organized as follows. Some related work is discussed in Section IT and in Section 111 we look at the radio propagation energy model. Section TV presents the network topology and energy

Over the past few years, mobile networks have emerged as a promising approach for future mobile IP applications. With limited frequency resources, designing an effective MAC (Medium Access Control) protocol is a hot challenge. IEEE 802.11b/g/a/n networks are currently the most popular wireless LAN products on the market [1]. The conventional IEEE 802.11b and 802.11g/a specification provide up to 11 and 54 Mbps data rates, respectively. However, the MAC protocol that they are based upon is the same and employs a CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance) protocol with binary exponential back-off. IEEE 802.11 DCF (Distributed Coordination Function) is the de facto MAC protocol for wireless LAN because of its simplicity and robustness [2,3]. Therefore, considerable research efforts have been put on the investigation of the DCF performance over wireless LAN [2]. With the successful deployment of IEEE 802.11a/b/g wireless LAN and the increasing demand for real-time applications over wireless, the IEEE 802.11n Working Group standardized a new MAC and PHY (Physical) layer specification to increase the bit rate to be up to 600 Mbps [3]. The throughput performance at the MAC layer can be improved by aggregating several frames before transmission [3]. Frame aggregation not only reduces the transmission time for preamble and frame headers, but also reduces the waiting time during CSMA/CA random backoff period for successive frame transmissions. The frame aggregation can be performed within different sub-layers. In 802.11n, frame aggregation can be performed either by A-MPDU (MAC Protocol Data Unit Aggregation) or A-MSDU (MAC Service Data Unit Aggregation). Although frame aggregation can increase the throughput at the MAC layer under ideal channel conditions, a larger aggregated frame will cause each station to wait longer before its next chance for channel access. Under errorprone channels, corrupting a large aggregated frame may waste a long period of channel time and lead to a lower MAC efficiency [4]. On the other hand, wireless LAN mobile stations that are defined as the stations that access the LAN while in motion are considered in this chapter. The previous paper analyzed the IEEE 802.11b/g/n MAC performance for wireless LAN with fixed stations, not for wireless LAN with mobile stations [5, 6, 7, 8, 9, 10]. On the contrary, Xi Yong [11] and Ha Cheol Lee [12] analyzed the MAC performance for IEEE 802.11 wireless LAN with mobile stations, but considered only IEEE 802.11 and 802.11g/a wireless LAN specification. So, this chapter summarizes all the reference papers and analyzes the IEEE 802.11b/g/a/n MAC performance for wireless LAN with fixed and mobile stations. In other words, we will present the analytical evaluation of saturation

Wireless Sensor Network (WSN) is used in various applications. Sensors acquire samples of physical data and send them to a central node in different topologies to process the data and makes decisions. A main performance factor for WSN is the battery life that depends on energy consumption on the sensor. To reduce the energy consumption, an energy efficient transmission technique is required. Multiple Input Multiple Output (MIMO) systems showed good utilization of channel characteristics. This leads to enhance the transmission and hence reduce energy consumed by the sensor. In MIMO systems multiple signals are combined at the transmitter and transmitted using multiple antennas. This provides each receiver the whole combined signal and hence, array processing techniques helps in getting better performance. To further enhance the transmission of data, a Low Density Parity Check (LDPC) Coded MIMO wireless sensor network is proposed. The system implements space diversity through Multiple Antennas and temporal diversity through LDPC code and uses a clustering procedure to optimize the forming of the MIMO system. Results showed that, if the number of sensors is greater than the number of receiving antennas, time or frequency multiplexing is possible to keep good performance for the devised system. And by controlling the encoder we can create a temporal and spatial code among the transmitted signals enhancing the BER results in longer battery life at sensor nodes.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

In conventional ways of fast responding and high performing model predictive control using Field Programmable Gate Arrays (FPGA), the approaches developed are applicable only to Single Input Single Output System (SISO). Many real time systems are Multiple Input Multiple Output (MIMO) systems and loop interaction is a major concern and has to be reduced in control of MIMO systems. Also, direct digital control with ability to solve the Quadratic Programming (QP) problem online, which can be applied to complex systems with fast response time and/or embedded applications and with limited computational resource for supervisory control approach, is required in many complex industrial MIMO systems. A novel direct digital control of Model predictive controller with FPGA for a MIMO system which considers and reduces loop interaction and which can also be implemented with very less investment is proposed here. The system was modeled from first principles and then simulated in Labview environment for MIMO system. Implementation of the system and response was verified for a stirred tank system. The proposed system has good performance in terms of reduction in loop interaction which is a major concern in implementation of controller for MIMO systems. Also, direct digital control of MIMO system instead of supervisory control was accomplished.

In this paper, we develop contention-based medium access control (MAC) schemes for both best-effort data transmissions and delay-sensitive multimedia transmissions over WLANs. A user detection module and a multi-rate adaptation module are proposed in the physical layer to assist in link differentiation. With these two modules, for best-effort data transmissions, a new distributed queuing MAC protocol (PALD-DQMP) is proposed. Based on different users' channel states, PALD-DQMP makes use of a distributed queuing system to schedule the transmissions. To support delay-sensitive multimedia transmissions, an enhanced PALD-DQMP (E-PALD-DQMP) is designed by providing twolevel optimized transmission scheduling for four access categories, thus eliminating both external and internal collisions among mobile stations. Simulation results show that our proposed protocols outperform the standard MAC protocols for both delaysensitive and best-effort traffics. AU these improvements are mainly contributed by the availability of cross-layer channel state information, and the consequent multi-rate adaptation scheme. © 2007 IEEE.

The free space optical (FSO) communication system has attracted many researchers from different countries, owning to its advantages such as high security, high speed and anti-interference. Among all kinds of the channels of the FSO communication system, the atmosphere channel is very difficult to deal with for two typical disadvantages at least. The one is the scintillation of the optical carrier intensity caused by the atmosphere turbulence and the other is the multipath effect by the optical scattering. A lot of studies have shown that the MIMO (Multiple Input Multiple Output) technology can overcome the scintillation of the optical carrier through the atmosphere effectively. So the background of this paper is a MIMO system which includes multiple optical transmitting antennas and multiple optical receiving antennas. A number of particles such as hazes, water droplets and aerosols exit in the atmosphere widely. When optical carrier meets these particles, the scattering phenomenon is inevitable, which leads to the multipath effect. As a result, a optical pulse transmitted by the optical transmitter becomes wider, to some extent, when it gets to the optical receiver due to the multipath effect. If the information transmission rate is quite low, there is less relationship between the multipath effect and the bit error rate (BER) of the communication system. Once the information transmission rate increases to a high level, the multipath effect will produce the problem called inter symbol inference (ISI) seriously and the bit error rate will increase severely. In order to take the advantage of the FSO communication system, the inter symbol inference problem must be solved. So it is necessary to use the channel equalization technology. This paper aims at deciding a equalizer and designing suitable equalization algorithm for a MIMO free space optical communication system to overcome the serious problem of bit error rate. The reliability and the efficiency of communication are two important indexes. For a MIMO communication system, there are two typical equalization methods. The first method, every receiving antenna has an independent equalizer without the information derived from the other receiving antennas. The second, the information derived from all of the receiving antennas mixes with each other, according to some definite rules, which is called space-time equalization. The former is discussed in this paper. The equalization algorithm concludes training mode and non training mode. The training mode needs training codes transmitted by the transmitter during the whole communication process and this mode reduces the communication efficiency more or less. In order to improve the communication efficiency, the blind equalization algorithm, a non training mode, is used to solve the parameter of the equalizer. In this paper, firstly, the atmosphere channel is described focusing on the scintillation and multipath effect of the optical carrier. Then, the structure of a equalizer of MIMO free space optical communication system is introduced. In the next part of this paper, the principle of the blind equalization algorithm is introduced. In addition, the simulation results are showed. In the end of this paper, the conclusions and the future work are discussed.

With the advanced physical layer techniques such as multiple-input and multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM), transmission real-time 2D/3D contents and applications becomes more and more necessary in wireless networks for the amazing growing in demand of customers. However, the low efficiency of medium access control (MAC) protocol degrades the performance of real-time traffic greatly in multihop, wireless and mobile environment. Focusing on supporting real-time multimedia traffic in cognitive wireless mesh networks (WMNs), an enhanced MAC protocol is proposed. And the contribution of this paper is twofold: (1) An efficient carrier sense multiple access with collision avoidance (CSMA/CA) compatible time division multiple access (TDMA)-like MAC protocol called T-MAC is proposed, which aims to improve the system performance by allocating more channel access time in centralized manner and decreasing overhead. (2) An optimal adaptive scheduling scheme is proposed to support real-time multimedia applications and guarantee QoS for different priority traffic, which aims to find the optimized schedule among all possible sequences of concurrent transmissions by minimizing the occupied resources. Detailed simulation results and comparison with IEEE 802.11e MAC scheme show that the proposed T-MAC can effectively improve quality of service (QoS) for multimedia traffic in terms of throughput, end-to-end delay and packet loss rate, which also manifests that T-MAC is an efficient multimedia applications transmission scheme for mobile terminals and MAPs in cognitive WMNs.

Since cognitive wireless network (CRN) has the characteristic of secondary use, it can enable the device to dynamically access available spectrum without interference to primary users (PUs), which can effectively alleviate contradiction between the lack of spectrum resources and the growing demand for wireless access. However, Medium Access Control (MAC) protocol as CRN core components, can achieve competition access of the licensed spectrum and coordination control, which will maximize spectrum utilization efficiency and network throughput. The contribution of this survey is threefold. First, we analyze the characteristics of the existed multi- channel MAC protocol in CRN; Second, according to the different ways of spectrum access in CRNs, the multi-channel MAC protocols are classified into time-slotted based MAC protocol, control channel based MAC protocol and hybrid MAC protocol, and the paper emphatically analyzed the advantages and disadvantages of these multi-channel MAC protocols; Finally, the paper explores the difficulties and the challenges of multi-channel MAC protocols design in cognitive wireless network.

Multiple-input multiple-output (MIMO) technology equips the transmitters with the multiple antennas. It can combine with energy harvesting (EH) to lift the spectrum efficiency and make use of a greener energy resource. A power grid is added to serve as a supplementary source to regulate the not-so-stable harvested energy supply of the system. Besides the MIMO technology being used, the power allocated to the user provided by both EH and the power grid is subject to the epoch power upper bound constraints. The background of these constraints comes from field requirements, such as avoiding the saturation of power allocated to the user(s), avoiding system-level out-of-band power leakage, and reducing interference with other transmitter(s) due to the non-linearity generated via the transmitting mechanisms to the user(s). The epoch power upper bound constraints make this problem more challenging, with the controllable power grid energy budget and its allocation. This paper applies our recently proposed geometric water-filling with group upper bounded power constraints and recursion machinery to form the proposed algorithm for solving the proposed throughput maximization problem. Our algorithm is precisely defined, and further provides the exact solution via the lower degree polynomial complexity. This point is very suitable for the massive MIMO system. To the best of our knowledge, no prior algorithm has been reported in the open literature to solve the targeted problem in this paper.