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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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. In this paper, the rate regions are studied for MIMO ad hoc networks. We first apply a framework developed for single antenna systems to MIMO systems, which gives the ultimate capacity region. Motivated by the fact that the ultimate capacity regions allow an optimization that may he unrealistic in some networks, a new concept of average rate region is proposed. We show the large gap between the ultimate capacity region and the new average rate region, while the latter is an upper bound on the performance of many existing ad hoc routing protocols. On the other hand, the average rate region also gives the average system performance over fading or random node positions. The outage capacity region is also defined. Through the study of the different rate regions, we show that the gain from multiple antennas for networks is similar to that for point-to-point communications. The gains obtained from multi-hop routing and spatial reuse are also shown for MIMO networks. 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. Smart antennas include a broad variety of antenna technologies ranging from the simple switched beams to the sophisticated digital adaptive arrays. While beam-forming antennas are good candidates for use in strong line of sight (LOS) environments, it is the multiple input multiple output (MIMO) technology that is best suited for multipath environments. In fact, the MIMO links exploit the multipath induced rich scattering to provide high spectral efficiencies. The focus of this work is to identify the various characteristics and tradeoffs of MIMO links that can be leveraged by routing layer protocols in rich multipath environments to improve their performance. To this end, we propose a routing protocol called MIR for ad-hoc networks with MIMO links, that leverages the various characteristics of MIMO links in its mechanisms to improve the network performance. We show the effectiveness of the proposed protocol by evaluating its performance through ns2 simulations for a variety of network conditions. We study the problem of distributed scheduling in multi-hop MIMO networks. We first develop a MIMO-pipe" model that provides the upper layers a set of rates and SINR requirements, which capture the rate-reliability tradeoff in MIMO communications. The main thrust of this study is then dedicated to developing CSMA-based MIMO-pipe scheduling under the SINR model. We choose the SINR model over the extensively studied matching or protocol-based interference models because it more naturally captures the impact of interference in wireless networks. The coupling among the links caused by the interference makes the problem of devising distributed scheduling algorithms particularly challenging. To that end, we explore CSMA-based MIMO-pipe scheduling, from two perspectives. First, we consider an idealized continuous time CSMA network. We propose a dual-band approach in which control messages are exchanged instantaneously over a channel separate from the data channel, and show that CSMA-based scheduling can achieve throughput optimality under the SINR model. Next, we consider a discrete time CSMA network. To tackle the challenge due to the coupling caused by interference, we propose a conservative" scheduling algorithm in which more stringent SINR constraints are imposed based on the MIMO-pipe model. We show that this suboptimal distributed scheduling can achieve an efficiency ratio bounded from below. 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. Multi-hop wireless networks facilitate applications in metropolitan area broadband, home multimedia, surveillance and industrial control networks. Many of these applications require high end-to- end throughput and or bounded delay. Random access link-layer protocols such as carrier sense multiple access (CSMA) which are widely used in single-hop networks perform poorly in the multi-hop regime and provide no end-to-end QoS guarantees. The primary causes for their poor performance are uncoordinated interference and unfairness in exclusive access of the shared wireless medium. Furthermore, random access schemes do not leverage spatial reuse effectively and require routes to be link- aware. In this paper, we propose and study MAX, a time-division- multiplexed resource allocation framework for multi-hop networks with regular topologies. MAX tiling delivers optimal end-to-end throughput across arbitrarily large regularly structured networks while providing bounded delay. It outperforms CSMA-based random access protocols by a factor of 5 to 8. The MAX approach also supports network services including flexible uplink and downlink bandwidth management, deterministic route admission control, and optimal gateway placement. MAX has been implemented on IEEE 802.15.3 embedded nodes and a test-bed of 50 nodes has been deployed both indoors and outdoors. This paper considers an interference network composed of K half-duplex single-antenna pairs of users who wish to establish bi-directional communication with the aid of a multi-input-multi-output (MIMO) half-duplex relay node. This channel is referred to as the “MIMO Wireless Switch” since, for the sake of simplicity, our model assumes no direct link between the two end nodes of each pair implying that all communication must go through the relay node (i.e., the MIMO switch). Assuming a delay-limited scenario, the fundamental limits in the high signal-to-noise ratio (SNR) regime is analyzed using the diversity-multiplexing tradeoff (DMT) framework. Our results sheds light on the structure of optimal transmission schemes and the gain offered by the relay node in two distinct cases, namely reciprocal and non-reciprocal channels (between the relay and end-users). In particular, the existence of a relay node, equipped with a sufficient number of antennas, is shown to increase the multiplexing gain; as compared with the traditional fully connected K-pair interference channel. To the best of our knowledge, this is the first known example where adding a relay node results in enlarging the pre-log factor of the sum rate. Moreover, for the case of reciprocal channels, it is shown that, when the relay has a number of antennas at least equal to the sum of antennas of all the users, static time allocation of decode and forward (DF) type schemes is optimal. On the other hand, in the non-reciprocal scenario, we establish the optimality of dynamic decode and forward in certain relevant scenarios. In ad hoc networks of nodes equipped with multiple antennas, the tradeoff between spatial multiplexing and diversity gains in each link impacts the overall network capacity. An optimal algorithm is developed for adaptive rate and power control for a communication link over multiple channels in a Poisson field of interferers. The algorithm and its analysis demonstrate that optimum area spectral efficiency is achieved when each communication link in a large distributed wireless network properly balances between diversity and multiplexing techniques. The channel adaptive algorithm is shown to be superior to traditional and static multi-antenna architectures, as well as to certain channel adaptive strategies previously proposed. Lastly, the adaptive rate control algorithm is coupled with an optimum frequency hopping scheme to achieve the maximum area spectral efficiency. We investigate the problem of designing delay-aware joint flow control, routing, and scheduling algorithms in general multi-hop networks for maximizing network utilization. Since the end-to-end delay performance has a complex dependence on the high-order statistics of cross-layer algorithms, earlier optimization-based design methodologies that optimize the long term network utilization are not immediately well-suited for delay-aware design. This motivates us in this work to develop a novel design framework and alternative methods that take advantage of several unexploited design choices in the routing and the scheduling strategy spaces. In particular, we reveal and exploit a crucial characteristic of back pressure-type controllers that enables us to develop a novel link rate allocation strategy that not only optimizes long-term network utilization, but also yields loop free multi-path routes between each source-destination pair. Moreover, we propose a regulated scheduling strategy, based on a token-based service discipline, for shaping the per-hop delay distribution to obtain highly desirable end-to-end delay performance. We establish that our joint flow control, routing, and scheduling algorithm achieves loop-free routes and optimal network utilization. Our extensive numerical studies support our theoretical results, and further show that our joint design leads to substantial end-to-end delay performance improvements in multi-hop networks compared to earlier solutions. 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. In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput "epsilon-close" to the optimal throughput in multi-hop wireless networks with a tradeoff of O(1 epsilon) in delay guarantees. The algorithm aims to solve a joint congestion control, routing, and scheduling problem in a multi-hop wireless network while satisfying per-flow average end-to-end delay guarantees and minimum data rate requirements. This problem has been solved for both backlogged as well as arbitrary arrival rate systems. Moreover, we discuss the design of a class of low-complexity suboptimal algorithms, the effects of delayed feedback on the optimal algorithm, and the extensions of the proposed algorithm to different interference models with arbitrary link capacities. We develop algorithms for joint IP layer routing and WDM logical topology reconfiguration in IP-over-WDM networks experiencing stochastic traffic. At the WDM layer, we associate a non-negligible tuning latency with WDM reconfiguration, during which time tuned transceivers cannot service backlogged data. The IP layer is modeled as a queueing system. We demonstrate that our algorithms achieve asymptotic throughput optimality by using frame-based maximum weight scheduling decisions. We study both deterministic and random frame durations. In addition to dynamically triggering WDM reconfiguration, our algorithms specify precisely how to route packets over the IP layer during the phases in which the WDM layer remains fixed. Our algorithms remain valid under a variety of optical layer constraints. We provide an analysis of the specific case of WDM networks with multiple ports per node. In order to gauge the delay properties of our algorithms, we conduct a simulation study and demonstrate an important tradeoff between WDM reconfiguration and IP layer routing. We find that multi-hop routing is extremely beneficial at low throughput levels, while single-hop routing achieves improved delay at high throughput levels. For a simple access network, we demonstrate through simulation the benefit of employing multi-hop IP layer routes. The MIMO wireless channel offers a rich ground for quality of service analysis. In this work, we present a stochastic network calculus analysis of a MIMO system, operating in spatial multiplexing mode, using moment generating functions (MGF). We quantify the spatial multiplexing gain, achieved through multiple antennas, for flow level quality of service (QoS) performance. Specifically we use Gilbert-Elliot model to describe individual spatial paths between the antenna pairs and model the whole channel by an @math -State Markov Chain, where @math depends upon the degrees of freedom available in the MIMO system. We derive probabilistic delay bounds for the system and show the impact of increasing the number of antennas on the delay bounds under various conditions, such as channel burstiness, signal strength and fading speed. Further we present results for multi-hop scenarios under statistical independence. 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. In this paper, the fundamental performance tradeoff of the delay-limited multiple-input multiple-output (MIMO) automatic retransmission request (ARQ) channel is explored. In particular, we extend the diversity-multiplexing tradeoff investigated by Zheng and Tse in standard delay-limited MIMO channels with coherent detection to the ARQ scenario. We establish the three-dimensional tradeoff between reliability (i.e., diversity), throughput (i.e., multiplexing gain), and delay (i.e., maximum number of retransmissions). This tradeoff quantifies the ARQ diversity gain obtained by leveraging the retransmission delay to enhance the reliability for a given multiplexing gain. Interestingly, ARQ diversity appears even in long-term static channels where all the retransmissions take place in the same channel state. Furthermore, by relaxing the input power constraint allowing variable power levels in different retransmissions, we show that power control can be used to dramatically increase the diversity advantage. Our analysis reveals some important insights on the benefits of ARQ in slow-fading MIMO channels. In particular, we show that 1) allowing for a sufficiently large retransmission delay results in an almost flat diversity-multiplexing tradeoff, and hence, renders operating at high multiplexing gain more advantageous; 2) MIMO ARQ channels quickly approach the ergodic limit when power control is employed. Finally, we complement our information-theoretic analysis with an incremental redundancy lattice space-time (IR-LAST) coding scheme which is shown, through a random coding argument, to achieve the optimal tradeoff(s). An integral component of the optimal IR-LAST coding scheme is a list decoder, based on the minimum mean-square error (MMSE) lattice decoding principle, for joint error detection and correction. Throughout the paper, our theoretical claims are validated by numerical results MIMO and cloud radio access network (C-RAN) are promising techniques for implementing future wireless communication systems, where a large number of antennas are deployed either being co-located at the base station or totally distributed at separate sites called remote radio heads (RRHs), both to achieve enormous spectrum efficiency and energy efficiency gains. Here, we consider a general antenna deployment method for wireless networks, termed multi-antenna C-RAN, where a flexible number of antennas can be equipped at each RRH to more effectively balance the performance and fronthaul complexity tradeoff beyond the conventional massive MIMO and single-antenna C-RAN. To coordinate and control the fronthaul traffic over multi-antenna RRHs, under the uplink communication setup, we propose a new “spatial-compression-and-forward (SCF)” scheme, where each RRH first performs a linear spatial filtering to denoise and maximally compress its received signals from multiple users to a reduced number of dimensions, then conducts uniform scalar quantization over each of the resulting dimensions in parallel, and finally sends the total quantized bits via a finite-rate fronthaul link to the baseband unit (BBU) for joint information decoding. Under this scheme, we maximize the minimum SINR of all users at the BBU by a joint resource allocation over the wireless transmission and fronthaul links. Specifically, each RRH determines its own spatial filtering solution in a distributed manner to reduce the signaling overhead with the BBU, while the BBU jointly optimizes the users’ transmit power, the RRHs’ fronthaul bits allocation, and the BBU’s receive beamforming with fixed spatial filters at individual RRHs. Numerical results show that, given a total number of antennas to be deployed, multi-antenna C-RAN with the proposed SCF and joint optimization significantly outperforms both massive MIMO and single-antenna C-RAN under practical fronthaul capacity constraints. Reducing power consumption and increasing battery life of nodes in an ad-hoc network requires an integrated power control and routing strategy. Power optimal routing selects the multi-hop links that require the minimum total power cost for data transmission under a constraint on the link quality. This paper studies optimal power routing under the constraint of a fixed end-to-end probability of error and compares the power optimal routes obtained with this criterion with those from the more commonly used fixed per hop error rate constraint. The comparison is carried out by looking at the properties of the power optimal graph, formed by the union of all the power optimal routes. The paper also provides algorithms to determine the power optimal routes. A wireless network with fading and a single source-destination pair is considered. The information reaches the destination via multiple hops through a sequence of layers of single-antenna relays. At high signal-to-noise ratio (SNR), the simple amplify-and-forward strategy is shown to be optimal in terms of degrees of freedom, because it achieves the degrees of freedom equal to a point-to-point multiple-input multiple-output (MIMO) system. Hence, the lack of coordination in relay nodes does not reduce the achievable degrees of freedom. The performance of this amplify-and-forward strategy degrades with increasing network size. This phenomenon is analyzed by finding the tradeoffs between network size, rate, and diversity. A lower bound on the diversity-multiplexing tradeoff for concatenation of multiple random Gaussian matrices is obtained. Also, it is shown that achievable network size in the outage formulation (short codes) is a lot smaller than the ergodic formulation (long codes).