MIMO technology is one of the most significant advances in the past decade to increase channel capacity and has a great potential to improve network capacity for mesh networks. In a MIMO-based mesh network, the links outgoing from each node sharing the common communication spectrum can be modeled as a Gaussian vector broadcast channel. Recently, researchers showed that dirty paper coding'' (DPC) is the optimal transmission strategy for Gaussian vector broadcast channels. So far, there has been little study on how this fundamental result will impact the cross-layer design for MIMO-based mesh networks. To fill this gap, we consider the problem of jointly optimizing DPC power allocation in the link layer at each node and multihop multipath routing in a MIMO-based mesh networks. It turns out that this optimization problem is a very challenging non-convex problem. To address this difficulty, we transform the original problem to an equivalent problem by exploiting the channel duality. For the transformed problem, we develop an efficient solution procedure that integrates Lagrangian dual decomposition method, conjugate gradient projection method based on matrix differential calculus, cutting-plane method, and subgradient method. In our numerical example, it is shown that we can achieve a network performance gain of 34.4 by using DPC.
Despite significant research progress in using MIMO for single-user communications, research on multi-user multi-hop MIMO networks is still in its inception stage. There are many open problems, and many areas are still poorly understood @cite_1 . Currently, the relatively well-studied research area of multi-user MIMO systems are cellular systems, which are single-hop and infrastructure-based. For multi-hop MIMO-based mesh networks, research results remain limited. In @cite_17 , Hu and Zhang studied the problem of joint medium access control and routing, with a consideration of optimal hop distance to minimize end-to-end delay. In @cite_6 , Sundaresan and Sivakumar used simulations to study various characteristics and tradeoffs (multiplexing gain vs. diversity gain) of MIMO links that can be leveraged by routing layer protocols in rich multipath environments to improve performance. In @cite_12 , proposed a distributed algorithm for MIMO-based multi-hop ad hoc networks, in which diversity and multiplexing gains of each link are controlled to achieve the optimal rate-reliability tradeoff. The optimization problem assumes fixed SINRs and fixed routes between source and destination nodes. However, in these works, there is no explicit consideration of per-antenna power allocation and their impact on upper layers. Moreover, DPC in cross-layer design has never been studied either.
@cite_1 @cite_12 @cite_6 @cite_17
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Large multiple-input multiple-output (MIMO) networks promise high energy efficiency, i.e., much less power is required to achieve the same capacity compared to the conventional MIMO networks if perfect channel state information (CSI) is available at the transmitter. However, in such networks, huge overhead is required to obtain full CSI especially for Frequency-Division Duplex (FDD) systems. To reduce overhead, we propose a downlink antenna selection scheme, which selects S antennas from M > S transmit antennas based on the large scale fading to serve K ≤ S users in large distributed MIMO networks employing regularized zero-forcing (RZF) precoding. In particular, we study the joint optimization of antenna selection, regularization factor, and power allocation to maximize the average weighted sum-rate. This is a mixed combinatorial and non-convex problem whose objective and constraints have no closed-form expressions. We apply random matrix theory to derive asymptotically accurate expressions for the objective and constraints. As such, the joint optimization problem is decomposed into subproblems, each of which is solved by an efficient algorithm. In addition, we derive structural solutions for some special cases and show that the capacity of very large distributed MIMO networks scales as O(KlogM) when M→∞ with K, S fixed. Simulations show that the proposed scheme achieves significant performance gain over various baselines. In this paper, we explore the utility of recently discovered multiple-antenna techniques (namely MIMO techniques) for medium access control (MAC) design and routing in mobile ad hoc networks. Specifically, we focus on ad hoc networks where the spatial diversity technique is used to combat fading and achieve robustness in the presence of user mobility. We first examine the impact of spatial diversity on the MAC design, and devise a MIMO MAC protocol accordingly. We then develop analytical methods to characterize the corresponding saturation throughput for MIMO multi-hop networks. Building on the throughout analysis, we study the impact of MIMO MAC on routing. We characterize the optimal hop distance that minimizes the end-to-end delay in a large network. For completeness, we also study MAC design using directional antennas for the case where the channel has a strong line of sight (LOS) component. Our results show that the spatial diversity technique and the directional antenna technique can enhance the performance of mobile ad hoc networks significantly. The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points (APs) per square mile has the potential to successfully meet such demand. In principle, distributed multiuser multiple-input-multiple-output (MU-MIMO) provides the best approach to infrastructure density increase since several access points are connected to a central server and operate as a large distributed multiantenna access point. This ensures that all transmitted signal power serves the purpose of data transmission, rather than creating interference. In practice, however, a number of implementation difficulties must be addressed, the most significant of which is aligning the phases of all jointly coordinated APs. In this paper, we propose AirSync, a novel scheme that provides timing and phase synchronization accurate enough to enable distributed MU-MIMO. AirSync detects the slot boundary such that all APs are time-synchronous within a cyclic prefix (CP) of the orthogonal frequency-division multiplexing (OFDM) modulation and predicts the instantaneous carrier phase correction along the transmit slot such that all transmitters maintain their coherence, which is necessary for multiuser beamforming. We have implemented AirSync as a digital circuit in the field programmable gate array (FPGA) of the WARP radio platform. Our experimental testbed, comprising four APs and four clients, shows that AirSync is able to achieve timing synchronization within the OFDM CP and carrier phase coherence within a few degrees. For the purpose of demonstration, we have implemented two MU-MIMO precoding schemes, Zero-Forcing Beamforming (ZFBF) and Tomlinson-Harashima Precoding (THP). In both cases, our system approaches the theoretical optimal multiplexing gains. We also discuss aspects related to the MAC and multiuser scheduling design, in relation to the distributed MU-MIMO architecture. To the best of our knowledge, AirSync offers the first realization of the full distributed MU-MIMO multiplexing gain, namely the ability to increase the number of active wireless clients per time-frequency slot linearly with the number of jointly coordinated APs, without reducing the per client rate. Multi-user MIMO (MU-MIMO) networks reveal the unique opportunities arising from a joint optimization of antenna combining techniques with resource allocation protocols. Furthermore, it brings robustness with respect to multipath richness, allowing for compact antenna spacing at the BS and, crucially, yielding the diversity and multiplexing gains without the need for multiple antenna user terminals. To realize these gains, however, the BS should be informed with the user's channel coefficients, which may limit practical application to TDD or low-mobility settings. To circumvent this problem and reduce feedback load, combining MU-MIMO with opportunistic scheduling seems a promising direction. The success for this type of scheduler is strongly traffic and QoS-dependent, however. We consider a large distributed MIMO system where wireless users with single transmit and receive antenna cooperate in clusters to form distributed transmit and receive antenna arrays. We characterize how the capacity of the distributed MIMO transmission scales with the number of cooperating users, the area of the clusters and the separation between them, in a line-of-sight propagation environment. We use this result to answer the following question: can distributed MIMO provide significant capacity gain over traditional multi-hop in large ad hoc networks with n source-destination pairs randomly distributed over an area A? Two diametrically opposite answers [24] and [26] have emerged in the current literature. We show that neither of these two results are universal and their validity depends on V the relation between the number of users n and √A λ, which we identify as the spatial degrees of freedom in the network. λ is the carrier wavelength. When √A λ ≥ n, there are n degrees of freedom in the network and distributed MIMO with hierarchical cooperation can achieve a capacity scaling linearly in n as in [24], while capacity of multihop scales only as √n. On the other hand, when √A λ ≤ √n as in [26], there are only √n degrees of freedom in the network and they can be readily achieved by multihop. Our results also reveal a third regime where √n ≤ √A λ ≤ n. Here, the number of degrees of freedom are smaller than n but larger than what can be achieved by multi-hop. We construct scaling optimal architectures for this intermediate regime. In this paper, we propose a cross layer optimization framework for multi-hop routing and resource allocation design in an orthogonal frequency division multiple access (OFDMA) based wireless mesh network. The network under consideration is assumed to consist of fixed mesh routers (or base station routers) inter-connected using OFDMA wireless links with some of the mesh routers functioning as gateways to a wired network. The objective of our cross-layer formulation is to allow joint determination of power control, frequency-selective OFDMA scheduling and multi-hop routing in order to maximize the minimum throughput that can be supported to all mesh routers. Results of our investigations under typical cellular deployment, propagation and channel model assumptions show that this approach achieves significant mesh throughput improvements primarily due to the following: (a) frequency selective scheduling with OFDMA which provides improved tone diversity thus allowing more efficient bandwidth utilization relative to single carrier methods; and (b) multi-hop routing which provides improved path diversity relative to single hop transmissions. Spatial multiple access holds the promise to boost the capacity of wireless networks when an access point has multiple antennas. Due to the asynchronous and uncontrolled nature of wireless LANs, conventional MIMO technology does not work efficiently when concurrent transmissions from multiple stations are uncoordinated. In this paper, we present the design and implementation of a crosslayer system, called SAM, that addresses the challenges of enabling spatial multiple access for multiple devices in a random access network like WLAN. SAM uses a chain-decoding technique to reliably recover the channel parameters for each device, and iteratively decode concurrent frames with misaligned symbol timings and frequency offsets. We propose a new MAC protocol, called CCMA, to enable concurrent transmissions by different mobile stations while remaining backward compatible with 802.11. Finally, we implement the PHY and MAC layer of SAM using the Sora high-performance software radio platform. Our evaluation results under real wireless conditions show that SAM can improve network uplink throughput by 70 with two antennas over 802.11. This paper explores the usage of cooperative multiple input multiple output (MIMO) technique to minimize energy consumption used to establish communications among distant nodes in a wireless sensor network (WSN). As energy depletion is an outstanding problem in WSN research field, a number of techniques aim to preserve such resource, especially by means of savings during communication among sensor nodes. One such wide used technique is multi-hop communication to diminish the energy required by a single node to transmit a given message, providing a homogeneous consumption of the energy resources among the nodes in the network. However, it is not the case that multi-hop is always more efficient than single-hop, even that it may represent a great depletion of a single node’s energy. In this paper a cooperative MIMO transmission technique for WSN is presented, which is compared to single-hop and multi-hop transmission ones, highlighting its advantages in relation to both. Simulation results support the statement about the utility in applying the proposed technique for energy saving purposes. Multi-user multiple-input multiple-output (MIMO) systems have been emerging and attracting considerable attention recently for its potential to substantially improve system capacity via space division multiple access. In this paper, we propose a distributed multi-user (MU) medium access control (MAC) protocol for wireless local area networks (WLANs) with MIMO capability, using a leakage-based preceding scheme. By exploiting the multi-user degree of freedom in a MIMO system to allow the access point (AP) to communicate with multiple users in the same frequency band simultaneously, the proposed MU MAC can effectively minimize the AP-bottleneck effect in legacy WLANs. We then develop an analytical model to study the performance of the proposed MU MAC, in terms of the maximum number of users that can be supported and the network throughput. The analysis and simulation results show that the proposed MU MAC significantly outperforms the single-user MAC. Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation. Extra antennas help by focusing energy into ever smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This article presents an overview of the massive MIMO concept and contemporary research on the topic. The equivalent-in-distribution (EiD)-based approach to the analysis of single-input-single-output (SISO) cellular networks for transmission over Rayleigh fading channels has recently been introduced [1]. Its rationale relies upon formulating the aggregate other-cell interference in terms of an infinite summation of independent and conditionally distributed Gaussian random variables (RVs). This approach leads to exact integral expressions of the error probability for arbitrary bi-dimensional modulations. In this paper, the EiD-based approach is generalized to the performance analysis of multiple-input-multiple-output (MIMO) cellular networks for transmission over Rayleigh fading channels. The proposed mathematical formulation allows us to study a large number of MIMO arrangements, including receive-diversity, spatial-multiplexing, orthogonal space-time block coding, zero-forcing reception and zero-forcing precoding. Depending on the MIMO setup, either exact or approximate integral expressions of the error probability are provided. In the presence of other-cell interference and noise, the error probability is formulated in terms of a two-fold integral. In interference-limited cellular networks, the mathematical framework simplifies to a single integral expression. As a byproduct, the proposed approach enables us to study SISO cellular networks for transmission over Nakagami- @math fading channels. The mathematical analysis is substantiated with the aid of extensive Monte Carlo simulations. We consider a MIMO multicell system wherein several Mobile Users (MUs) ask for computation offloading to a common cloud server through their femto-access points. We formulate the computation offloading problem as a joint optimization of the radio resources??the transmit precoding matrices of the MUs??and the computational resources??the CPU cycles second assigned by the cloud to each MU??in order to minimize the overall users' energy consumption while meeting the latency constraints imposed by the applications running on the MUs. The resulting optimization problem is nonconvex (in the objective function and the constraints), and there are constraints coupling all the optimization variables. To cope with the nonconvexity, we hinge on successive convex approximation techniques and propose an iterative algorithm converging to a local optimal solution of the original nonconvex problem. The algorithm is also suitable for a parallel implementation across the access point, with limited coordination signaling with the cloud. Numerical results show that the proposed joint optimization yields significant energy savings with respect to more traditional schemes performing a separate optimization of the radio and computational resources. The massive multiple-input multiple-output (MIMO) technology has great potential to manage the rapid growth of wireless data traffic. Massive MIMO achieves tremendous spectral efficiency by spatial multiplexing many tens of user equipments (UEs). These gains are only achieved in practice if many more UEs can connect efficiently to the network than today. As the number of UEs increases, while each UE intermittently accesses the network, the random access functionality becomes essential to share the limited number of pilots among the UEs. In this paper, we revisit the random access problem in the Massive MIMO context and develop a reengineered protocol, termed strongest-user collision resolution (SUCRe). An accessing UE asks for a dedicated pilot by sending an uncoordinated random access pilot, with a risk that other UEs send the same pilot. The favorable propagation of massive MIMO channels is utilized to enable distributed collision detection at each UE, thereby determining the strength of the contenders’ signals and deciding to repeat the pilot if the UE judges that its signal at the receiver is the strongest. The SUCRe protocol resolves the vast majority of all pilot collisions in crowded urban scenarios and continues to admit UEs efficiently in overloaded networks. This paper analyzes the performance of information and energy beamforming in multiple-input multiple- output (MIMO) wireless communications systems, where a self-powered multi-antenna hybrid access point (AP) coordinates wireless information and power transfer (WIPT) with an energy-constrained multi-antenna user terminal (UT). The wirelessly powered UT scavenge energy from the hybrid AP radio-frequency (RF) signal in the downlink (DL) using the harvest-then-transmit protocol, then uses the harvested energy to send its information to the hybrid AP in the uplink (UL). To maximize the overall signal-to-noise ratio (SNR) as well as the harvested energy so as to mitigate the severe effects of fading and enable long-distance wireless power transfer, information and energy beamforming is investigated by steering the transmitted information and energy signals along the strongest eigenmode. To this end, exact and lower-bound expressions for the outage probability and ergodic capacity are presented in closed-form, through which the throughput of the delay- constrained and delay-tolerant transmission modes are analyzed, respectively. Numerical results sustained by Monte Carlo simulations show the exactness and tightness of the proposed analytical expressions. The impact of various parameters such as energy harvesting time, hybrid AP transmit power and the number of antennas on the system throughput is also considered. The capacity and robustness of cellular MIMO systems is very sensitive to other-cell interference which will in practice necessitate network level interference reduction strategies. As an alternative to traditional static frequency reuse patterns, this paper investigates intercell scheduling among neighboring base stations. We show analytically that cooperatively scheduled transmission, which is well within the capability of present systems, can achieve an expanded multiuser diversity gain in terms of ergodic capacity as well as almost the same amount of interference reduction as conventional frequency reuse. This capacity gain over conventional frequency reuse is O (M t square-root of log Ns) for dirty paper coding and O (min (Mr, Mt) square-root of log Ns) for time division, where Ns is the number of cooperating base stations employing opportunistic scheduling in an M t x M r MIMO system. From a theoretical standpoint, an interesting aspect of this analysis comes from an altered view of multiuser diversity in the context of a multi-cell system. Previously, multiuser diversity capacity gain has been known to grow as O(log log K), from selecting the maximum of K exponentially-distributed powers. Because multicell considerations such as the positions of the users, lognormal shadowing, and pathless affect the multiuser diversity gain, we find instead that the gain is O(square-root of 2logic K), from selecting the maximum of a compound Iognormal-exponential distribution. Finding the maximum of such a distribution is an additional contribution of the paper. We provide an overview of the extensive results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about the underlying time-varying channel model and how well it can be tracked at the receiver, as well as at the transmitter. More realistic assumptions can dramatically impact the potential capacity gains of MIMO techniques. For time-varying MIMO channels there are multiple Shannon theoretic capacity definitions and, for each definition, different correlation models and channel information assumptions that we consider. We first provide a comprehensive summary of ergodic and capacity versus outage results for single-user MIMO channels. These results indicate that the capacity gain obtained from multiple antennas heavily depends on the available channel information at either the receiver or transmitter, the channel signal-to-noise ratio, and the correlation between the channel gains on each antenna element. We then focus attention on the capacity region of the multiple-access channels (MACs) and the largest known achievable rate region for the broadcast channel. In contrast to single-user MIMO channels, capacity results for these multiuser MIMO channels are quite difficult to obtain, even for constant channels. We summarize results for the MIMO broadcast and MAC for channels that are either constant or fading with perfect instantaneous knowledge of the antenna gains at both transmitter(s) and receiver(s). We show that the capacity region of the MIMO multiple access and the largest known achievable rate region (called the dirty-paper region) for the MIMO broadcast channel are intimately related via a duality transformation. This transformation facilitates finding the transmission strategies that achieve a point on the boundary of the MIMO MAC capacity region in terms of the transmission strategies of the MIMO broadcast dirty-paper region and vice-versa. Finally, we discuss capacity results for multicell MIMO channels with base station cooperation. The base stations then act as a spatially diverse antenna array and transmission strategies that exploit this structure exhibit significant capacity gains. This section also provides a brief discussion of system level issues associated with MIMO cellular. Open problems in this field abound and are discussed throughout the paper. Explicit code constructions for multiple-input multiple-output (MIMO) multiple-access channels (MAC) with K users are presented in this paper. The first construction is dedicated to the case of symmetric MIMO-MAC where all the users have the same number of transmit antennas nt and transmit at the same level of per-user multiplexing gain r. Furthermore, we assume that the users transmit in an independent fashion and do not cooperate. The construction is systematic for any values of K, nt and r. It is proved that this newly proposed construction achieves the optimal MIMO-MAC diversity-multiplexing gain tradeoff (DMT) provided by Tse at high-SNR regime. In the second part of the paper we take a further step to investigate the MAC-DMT of a general MIMO-MAC where the users are allowed to have different numbers of transmit antennas and can transmit at different levels of multiplexing gain. The exact optimal MAC-DMT of such channel is explicitly characterized in this paper. Interestingly, in the general MAC-DMT, some users might not be able to achieve their single-user DMT performance as in the symmetric case, even when the multiplexing gains of the other users are close to 0. Detailed explanations of such unexpected result are provided in this paper. Finally, by generalizing the code construction for the symmetric MIMO-MAC, explicit code constructions are provided for the general MIMO-MAC and are proved to be optimal in terms of the general MAC-DMT. Multiple-input multiple-output (MIMO) is one form of the smart antenna technology that uses multiple antennas at both the transmitter and receiver to improve communication performance. In this paper, we investigate the problem of medium access control in wireless local area networks (WLANs) with downlink multi-user MIMO (DL MU MIMO) capability. We propose a CSMA CA MAC protocol with three response mechanisms for DL MU MIMO and compare the performance of DL MU MIMO with the beam-forming (BF) based approach. A novel per-station weighted queuing mechanism is proposed to mitigate the hidden node problem in the network. Performance analysis and simulation study both show that the proposed DL MU MIMO mechanism incurs low overhead and provides significant throughput performance gain over BF based approach in high SNR scenarios. It is well known that multiple-input multiple-output (MIMO) techniques can bring numerous benefits, such as higher spectral efficiency, to point-to-point wireless links. More recently, there has been interest in extending MIMO concepts to multiuser wireless systems. Our focus in this paper is on network MIMO, a family of techniques whereby each end user in a wireless access network is served through several access points within its range of influence. By tightly coordinating the transmission and reception of signals at multiple access points, network MIMO can transcend the limits on spectral efficiency imposed by cochannel interference. Taking prior information-theoretic analyses of network MIMO to the next level, we quantify the spectral efficiency gains obtainable under realistic propagation and operational conditions in a typical indoor deployment. Our study relies on detailed simulations and, for specificity, is conducted largely within the physical-layer framework of the IEEE 802.16e Mobile WiMAX system. Furthermore, to facilitate the coordination between access points, we assume that a high-capacity local area network, such as Gigabit Ethernet, connects all the access points. Our results confirm that network MIMO stands to provide a multiple-fold increase in spectral efficiency under these conditions. We develop a general framework for the analysis of a broad class of point-to-point linear multiple-input multiple-output (MIMO) transmission schemes in decentralized wireless ad hoc networks. New general closed-form expressions are derived for the outage probability, throughput and transmission capacity. For the throughput, we investigate the optimal number of data streams in various asymptotic regimes, which is shown to be dependent on different network parameters. For the transmission capacity, we prove that it scales linearly with the number of antennas, provided that the number of data streams also scales linearly with the number of antennas, in addition to meeting some mild technical conditions. We also characterize the optimal number of data streams for maximizing the transmission capacity. To make our discussion concrete, we apply our general framework to investigate three popular MIMO schemes, each requiring different levels of feedback. In particular, we consider eigenmode selection with MIMO singular value decomposition, multiple transmit antenna selection, and open-loop spatial multiplexing. Our analysis of these schemes reveals that significant performance gains are achieved by utilizing feedback under a range of network conditions.