An emerging trend of next generation communication systems is to provide network edges with additional capabilities such as additional storage resources in the form of caches to reduce file delivery latency. To investigate this aspect, we study the fundamental limits of a cache-aided wireless network consisting of one central base station, M transceivers and K receivers from a latency-centric perspective. We use the normalized delivery time (NDT) to capture the per-bit latency for the worst-case file request pattern at high signal-to-noise ratios (SNR), normalized with respect to a reference interference-free system with unlimited transceiver cache capabilities. For various special cases that satisfy K+M≤4, we establish the optimal tradeoff between cache storage and latency. This is facilitated through establishing a novel converse (for arbitrary M and K) and an achievability scheme on the NDT. Our achievability scheme is a synergistic combination of multicasting, zero-forcing beamforming and interference alignment.

By performing fog computing, a device can offload delay-tolerant computationally demanding tasks to its peers for processing, and the results can be returned and aggregated. In distributed wireless networks, the challenges of fog computing include lack of central coordination, selfish behaviors of devices, and multi-hop signaling delays, which can result in outdated network knowledge and prevent effective cooperations beyond one hop. This paper presents a new approach to enable cooperations of N selfish devices over multiple hops, where selfish behaviors are discouraged by a tit-for-tat mechanism. The titfor-tat incentive of a device is designed to be the gap between the helps (in terms of energy) the device has received and offered; and indicates how much help the device can offer at the next time slot. The tit-for-tat incentives can be evaluated at every device by having all devices broadcast how much help they offered in the past time slot, and used by all devices to schedule task offloading and processing. The approach achieves asymptotic optimality in a fully distributed fashion with a timecomplexity of less than O(N2). The optimality loss resulting from multi-hop signaling delays and consequently outdated titfor-tat incentives is proved to asymptotically diminish. Simulation results show that our approach substantially reduces the timeaverage energy consumption of the state of the art by 50% and accommodates more tasks, by engaging devices hops away under multi-hop delays.

Mobile edge computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can get complex tasks offloaded to and processed at powerful infrastructure. Scheduling is challenging due to stochastic task arrivals and wireless channels, congested air interface, and more prominently, prohibitive feedbacks from thousands of devices. In this paper, we generate asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks. A perturbed Lyapunov function is designed to stochastically maximize a network utility balancing throughput and fairness. A knapsack problem is solved per slot for the optimal schedule, provided up-to-date knowledge on the data and energy backlogs of all devices. The knapsack problem is relaxed to accommodate out-of-date network states. Encapsulating the optimal schedule under up-to-date network knowledge, the solution under partial out-of-date knowledge preserves asymptotic optimality, and allows devices to self-nominate for feedback. Corroborated by simulations, our approach is able to dramatically reduce feedbacks at no cost of optimality. The number of devices that need to feed back is reduced to less than 60 out of a total of 5000 IoT devices.

In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that the minimum number of users required to achieve a target degrees-of-freedom can be fundamentally reduced, i.e., the fundamental user scaling law can be improved by using the ODIA, compared with the existing downlink IA schemes. In addition, we adopt a limited feedback strategy in the ODIA framework, and then analyze the number of feedback bits required for the system with limited feedback to achieve the same user scaling law of the ODIA as the system with perfect channel state information. We also modify the original ODIA in order to further improve the sum-rate, which achieves the optimal multiuser diversity gain, i.e., log log N, per spatial stream even in the presence of downlink inter-cell interference, where N denotes the number of users in a cell. Simulation results show that the ODIA significantly outperforms existing interference management techniques in terms of sum rate in realistic cellular environments. Note that the ODIA operates in a non-collaborative and decoupled manner, i.e., it requires no information exchange among BSs and no iterative beamformer optimization between BSs and users, thus leading to an easier implementation.

Opportunistic interference alignment (OIA) has been known to asymptotically achieve the optimal degrees-of-freedom (DoF) in multi-input multi-output (MIMO) interfering multiple-access channels (IMACs) as the number of users scales with signal-to-noise ratio, even though no collaboration between base stations (BSs) is assumed. In some previous studies on OIA, the zero-forcing (ZF) receiver has been used at the BSs since it is sufficient to achieve the optimal DoF. In this paper, we propose a simple minimum distance (MD) receiver in a MIMO IMAC model, enabling us to implement the OIA scheme with no information of other-cell interfering links. Surprisingly, we show that as the number of users increases, the MD receiver not only guarantees the optimal DoF but also asymptotically achieves the optimal capacity obtained along with full information of other-cell interfering links. Simulation results indicates that the MD receiver indeed outperforms the conventional ZF receiver even in practical cellular setups.

We introduce an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that compared to the existing downlink IA schemes, the minimum number of users required to achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e., the fundamental user scaling law can be improved, by using the ODIA. In addition, we introduce a limited feedback strategy in our ODIA framework, and then analyze the minimum number of feedback bits required to obtain the same performance as that of the ODIA assuming perfect feedback.

We propose a low-complexity minimum mean square error (MMSE) transmit filter design for the coordinated beamforming (CB) in the coordinated multipoint (CoMP) under the practical per-antenna power constraint (PAPC). The proposed design is based on the nonlinear Gauss-Seidel type algorithm in which the transmit filters for given receive filters are computed by iteratively updating the beamformer of each transmit antenna using simple closed-form expressions. The proposed approach can significantly reduce the overall complexity of the alternating optimization while preserving the optimality in the MSE sense.

Distributed sum-rate-maximizing covariance matrices design for full-duplex multi-input multi-output communication is considered, where the information of the loopback interference channels cannot be exchanged reliably due to their large dynamic ranges. We propose a structured covariance matrices design which finds the optimal balance between the two solutions in the extremes of the weak and strong self-interference through a single-parameter optimization. We further propose a low-complexity null projection matrix design algorithm, in which the solution in the strong self-interference regime is designed in the sense to maximize the received channel gain. Exploiting the well-posed structure, the proposed scheme nearly achieves the sum-rate of the previous scheme based on the gradient projection with significantly less amount of inter-node iterations, yielding an increased effective sum-rate and reduced overall complexity for the practial channel block lengths.

We consider the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N users having L antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by SNR(K-1)S, where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to SNR(K-1)S-L+1through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

We investigate the transmit beamforming with antenna selection and power combining for multiple antenna systems with practical per-antenna power constraint. We consider that more than one power amplifier (PA) outputs can potentially be combined by using power combiners, such as hybrid combiners, and fed into antennas with stronger channel gains in order to achieve better channel coupling efficiency. The SNR gain of the proposed scheme is analyzed for two different power combining scenarios. For a general number of PAs and transmit antennas, we present an efficient algorithm to find the optimal antenna selection and the power combining vector for multiple-input single-output (MISO) systems, and discuss its extension to general multiple-input multiple-output (MIMO) systems. Numerical results show that the proposed design provides an efficient way to reduce the large SNR loss due to the strong channel imbalance in the MIMO systems.

We study a transmit beamforming for multiple antenna systems under the per-antenna power and the equivalent isotropic radiation power (EIRP) constraints. Finding the optimal beamforming vector maximizing SNR in such case is known to be NP-hard, and its semi-definite programming (SDP) approximation can be still complex due to the large number of the inequality constraints. This work considers a low complexity transmit beamforming technique, called Golay beamforming, based on the structured codebook consisting of the Golay sequences with the bounded EIRP guarantee. We discuss the specific structure and the performance bounds of the Golay beamforming, and propose the weighted Golay beamforming which can further improve the received SNR by using a specific set of the weighted Golay sequences which enjoys the same bounded low EIRP. Numerical results show that the proposed Golay beamforming provides an efficient low complexity solution with the graceful performance degradation under moderate EIRP constraints, and can be further improved by the weighted Golay beamforming.

We consider a new opportunistic interference alignment (OIA) for the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N mobile stations (MSs) having L antennas each. In this paper, we propose three OIA techniques: antenna selection-based OIA, singular value decomposition (SVD)-based OIA, and vector-quantized (codebook-based) OIA. Then, their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting MSs per cell. As our main result, it is shown that the antenna selection-based OIA does not fundamentally change the user scaling required to achieve KS DoF if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case. In contrast, it is shown that the SVD-based OIA can greatly reduce the required user scaling to SNR(K-1) S-L+1through optimizing weight vectors at each MS. Furthermore, we show that the vector-quantized OIA can achieve the same user scaling as the SVD-based OIA case if the codebook size is beyond a certain value. For the vector-quantized OIA, we analyze a fundamental tradeoff between the quantization level (i.e., codebook size) and the required user scaling.

We study the outage performance of an amplify-and-forward (AF) cooperation with full duplex relaying (FDR). When there exists a non-negligible direct link or residual self interference (RSI), full duplex relaying turns the effective channel into a frequency selective channel. Assuming minimum mean squared error decision feedback equalization (MMSE-DFE) at the destination, we derive tight closed-form bounds on the outage probability expression for AF-FDR, and study the effect of the direct link and the RSI in the optimal duplex mode selection. It is shown that under a strong direct link, FDR becomes less beneficial due to the persistent noise amplification. Furthermore, equalizing the RSI at the destination is shown to provide more graceful performance degradation compared to a simple receiver considered in previous works, which treats the RSI as noise.

We derive a new sum-rate lower bound of the multiuser multi-input multi-output (MU-MIMO) cellular two-way relay channel (cTWRC) which is composed of a base station (BS) and a relay station (RS), both with multiple antennas, and non-cooperative mobile stations (MSs), each with a single antenna. In the first phase, we show that network coding based on decode-and-forward relaying can be generalized to arbitrary input cardinality through proposed lattice code-aided linear precoding, despite the fact that precoding is permitted only at the BS due to non-cooperation among the MSs. In addition, a new sum-rate lower bound for the second phase is derived by showing that the two spatial decoding orders at the BS and MSs for one-sided zero-forcing dirty-paper-coding must be identical. From the fundamental gain of network coding, our sum-rate lower bound achieves the full multiplexing gain regardless of the number of antennas at the BS or RS, and strictly exceeds the previous lower bound which is based on traditional multiuser decoding in the first phase. Furthermore, it is shown that our lower bound asymptotically achieves the sum-rate upper bound in the presence of signal-to-noise ratio (SNR) asymmetry in high SNR regime, and sufficient conditions for this SNR asymmetry are drawn.

Lattice-reduction-aided precoding (LRP) provides near-capacity rates with the use of low-complexity linear receivers for coded multiple-input multiple-output (MIMO) systems. However, a large amount of feedback in the feedback for an integer or binary precoding matrix has been a bottleneck in its implementation. In this paper, we propose a codebook-based LRP scheme for limited-feedback coded MIMO systems. The proposed LRP scheme follows the fundamentals of the previous LRP scheme that employed multilevel binary coset coding so that the precoding matrix is binary. In the proposed LRP scheme, the conventional precoding matrix obtained from the Lenstra-Lenstra-Lovasz algorithm is modified to specific forms that are predefined in a codebook set. The new precoding matrix is selected such that the lower bound on the capacity is maximized for a given codebook set, while the codebook set is designed offline such that the upper bound of the average capacity loss induced by the limitation on the codebook size is minimized. The simulation results show that the proposed LRP scheme nearly achieves the achievable rate of the conventional LRP scheme with a greatly reduced amount of feedback.

To evaluate the unitary integrals, such as the well-known Harish–Chandra–Itzykson–Zuber integral, character expansions were developed by Balantekin, where the matrix integrand is a group member; i.e., a square matrix with a nonzero determinant. Recently, this method has been exploited to derive the joint eigenvalue distributions of the Wishart matrices; i.e.,${\bf H}{\bf H}^{\ast}$where${\bf H}$is the complex Gaussian random channel matrix of a multiple-input multiple-output (MIMO) system. The joint eigenvalue distributions are used to calculate the moment generating function of the mutual information (ergodic capacity) of a MIMO channel. In this paper, we show that the previous integration framework presented in the literature is not correct, and results in incorrect joint eigenvalue distributions for the Ricean and full-correlated Rayleigh MIMO channels. We develop a new framework to apply the character expansions for integrations over the unitary group, involving general rectangular complex matrices in the integrand. We derive the correct distribution functions and use them to obtain the capacity of the Ricean and correlated Rayleigh MIMO systems in a unified and straightforward approach. The integration technique proposed in this paper is general enough to be used for other unitary integrals in engineering, mathematics, and physics.

The interference channel achievable rate region is presented when the interference is treated as noise. The formulation starts with the 2-user channel, and then extends the results to the n-user case. The rate region is found to be the convex hull of the union of n power control rate regions, where each power control rate region is upperbounded by a (n-1)-dimensional hyper-surface characterized by having one of the transmitters transmitting at full power. The convex hull operation lends itself to a time-sharing operation depending on the convexity behavior of those hyper-surfaces. In order to know when to use time-sharing rather than power control, the paper studies the hyper-surfaces convexity behavior in details for the 2-user channel with specific results pertaining to the symmetric channel. It is observed that most of the achievable rate region can be covered by using simple On/Off binary power control in conjunction with time-sharing. The binary power control creates several corner points in the n-dimensional space. The crystallized rate region, named after its resulting crystal shape, is hence presented as the time-sharing convex hull imposed onto those corner points; thereby offering a viable new perspective of looking at the achievable rate region of the interference channel.

For a receiver that observes a mixture of desired and interfering multiple-input multiple-output (MIMO) transmissions, not all interference has the same severity: its effect is modulated by the degree of alignment between the eigenspaces of the desired and undesired channel matrices. An analytical channel model is proposed to account for this effect. Two metrics of eigenspace compatibility are studied, and a method to generate channels of a given degree of compatibility is derived. The resulting model is parameterized using radio channel measurement data, and an implementation recipe for immediate use of the model is provided.

In multiple-input multiple-output (MIMO) systems, the propagation channels can be characterized by their spatial structure, described by the (complex-valued) channel correlation. Accordingly, also interference in MIMO systems is likely to occur in a spatially structured, correlated way. We discuss that structured spatial interference affects mutual information under interference, depending on the eigenspace alignment between the channel of the desired signal and the channel carrying the interference. Intuitively, worst-case interference occurs, when the channels from the intended signal and the interference show a similar spatial structure. In contrast, least hurtful interference is encountered when these channels are maximally non-aligned. In this paper, we develop an analytical channel model generating multi-user MIMO channels with a given degree of severity of interference, described by the alignment of the channels' eigenspaces. Using radio channel measurements, we parameterize our model to reflect realistic scenarios.

A multiple-input multiple-output two-way relay channel consisting of two communication nodes and a full-duplex relay node in which no direct link exists between the two communication nodes is considered. We propose an achievable scheme that employs horizontally encoded lattice codes combined with generalized singular value decomposition-based precoding for the first phase. The second phase of the proposed scheme follows the fundamentals of the previous scheme, which uses vertically encoded structural bining, with the only difference that the added codeword of the two codewords from the communication nodes, instead of those two individual codewords, is decoded and retransmitted in the proposed scheme. We show that the proposed scheme achieves the cut-set bound asymptotically as the signal-to-noise ratios of the channels tend to infinity.

We consider secret key agreement based on radio propagation characteristics in two-way relaying system where two legitimate parties named Alice and Bob communicate with each other via a relay. In this system, Alice and Bob share secret keys generated from their radio propagation characteristics by the help of the relay. In this paper, we present two secret key agreement schemes: an amplify-and-forward (AF) scheme and a multiple-access amplify-and-forward (MA-AF) scheme. In both of the schemes, the basic idea is to share the effective fading coefficient between Alice and Bob and use it as the source of secret keys. The AF scheme is based on a conventional amplify-and-forward two-way relaying method, while the MA-AF scheme utilizes the inherent combining of signals provided by simultaneous transmissions over a multiple-access channel in order to share the secret keys more securely efficiently. We analyze eavesdropping strategy in terms of eavesdropper's location and show that if the eavesdropper is located near the relay and can receive signals from the relay without multipath fading and noise, the AF scheme is not secure. Simulation results show that the MA-AF scheme is more secure and efficient than the AF scheme.

This letter proposes a new approach to achieve the maximum diversity gain in the vertical Bell Laboratories Layered Space-Time (V-BLAST) system over multiple-input multiple-output (MIMO) Rayleigh channels. First, we will briefly review the modulation diversity scheme based on real-valued multidimensional rotated constellations that has been proposed to obtain high diversity orders for single-input single-output (SISO) systems. Then, this letter extends the modulation diversity scheme to V-BLAST MIMO systems in order to achieve the maximum diversity gain without additional power or bandwidth consumption. The proposed method is particularly suitable for MIMO applications which employ channel codes with high rate in order to support high spectral efficiency.

Treating the interference as noise in the n-user interference channel, the paper describes a novel approach to the rates region, composed by the time-sharing convex hull of 2n-1 corner points achieved through On/Off binary power control. The resulting rates region is denoted crystallized rates region. By treating the interference as noise, the n-user rates region frontiers has been found in the literature to be the convex hull of n hyper-surfaces. The rates region bounded by these hyper- surfaces is not necessarily convex, and thereby a convex hull operation is imposed through the strategy of time-sharing. This paper simplifies this rates region in the n-dimensional space by having only an On/Off binary power control. This consequently leads to 2n- 1 corner points situated within the rates region. A time-sharing convex hull is imposed onto those corner points, forming the crystallized rates region. The paper focuses on game theoretic concepts to achieve that crystallized convex hull via correlated equilibrium. In game theory, the correlated equilibrium set is convex, and it consists of the time-sharing mixed strategies of the Nash equilibriums. In addition, the paper considers a mechanism design approach to carefully design a utility function, particularly the Vickrey-Clarke-Groves auction utility, where the solution point is situated on the correlated equilibrium set. Finally, the paper proposes a self learning algorithm, namely the regret- matching algorithm, that converges to the solution point on the correlated equilibrium set in a distributed fashion.

Since multi-antenna (MIMO) systems are becoming more popular thanks to their inherent potential for capacity improvement, interference from MIMO transceivers is an increasingly serious concern. Spatial multiplexing schemes are particularly vulnerable to multi-user interference. Fortunately, this interference can be mitigated, when the channel matrices show a sufficient spatial separation. In this paper, we quantify the separability of multi-user MIMO channels using actual measurements in a scenario where a single outdoor base station transmits to two indoor mobile receivers. To quantify the spatial distance between the two users, we compare the spatial correlation matrices using two simple measures: (i) matrix collinearity, and (ii) the condition number ratio. Both measures are directly linked to MIMO system performance. Our measurement-based evaluations demonstrate that the downlink channels of different users can have a significantly different spatial structure, even when the users are in the same room. This leads to the following conclusions: (i) new multi-user MIMO models are needed to describe the spatial characteristics of different users, and (ii) spatial interference can be well managed by appropriate scheduling and precoding algorithms.

In this paper, an empirical model of the indoor distributed channel is presented. In particular, the shadowing and fading statistics are extracted from experimental data at 2.45 GHz in stationary and mobile scenarios. Highlights of the paper include a separate model for static and dynamic shadowing, a model for shadowing correlation, as well as a single analytical distribution of small-scale fading for various types of indoor node mobility.

In this paper, the capacity of several outdoor-to-indoor relay schemes has been investigated using real-world measurements at 2.45 GHz. The considered scenario encompasses an outdoor base station, possibly using multiple antennas, communicating via two hops to distributed single antenna terminals located inside a building. The single-antenna relays are located along the so-called best wall. Capacity results show that in most cases, relaying techniques increase the capacity, even when constraining the global power expense of the network. Considering a combining scheme using the source-to-destination in addition to the relay link does not bring huge benefits for the measured outdoor-to-indoor channels. The best performance is obtained in a relay-and-forward scheme using multiple cooperative relays.

We consider a wireless downlink system with one transmit base station (BS) and two receive subscriber stations (SS1 and SS2) in full frequency reuse. The primary subscriber (SS1) is served in two hops via a relay station (RS). The second subscriber (SS2) is located relatively close to both BS and RS. In a conventional paradigm, SS2 can not receive its message from BS when either BS or RS serves SSI, since the transmissions for SSI cause strong interference at SS2. To improve system throughput, we propose an interference cancellation scheme at SS2 that allows BS to serve SS2 while RS relays. Exploiting the identity of the interfering messages in the two hops, SS2 overhears the interfering message at its initial transmission and cancels its interference latter. Theoretical analysis and realistic simulations show that the proposed scheme can significantly and practically boost system throughput.

In this paper, we show that the use of cyclic delay diversity (CDD) on the downlink (DL) can improve the performance of uplink (UL) diversity methods such as antenna selection in a time-division duplexing (TDD) system. An analytical framework for showing why CDD transmission on the DL improves UL diversity transmission in TDD system is provided. The analysis is used to quantify the gain in the UL received signal-to-noise ratio (SNR) when DL CDD is used. The analytical results show that for a 2times2 MIMO system that uses DL CDD, UL transmit diversity based on antenna selection improves the average UL SNR by 0.41 dB relative to the case when CDD is not being applied at the BS transmitter and improves the 1% CDF UL SNR by 1.58 dB. Measurement-based analysis validates the analytical results using measured frequency response of a MIMO system using a wideband channel sounder.

This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI) in a flat-fading channel. In particular, we optimize the relay weights jointly to maximize the received signal-to-noise ratio (SNR) at the destination terminal with both individual and total power constraints at the relays. We show that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system. Another main contribution of this letter is a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush–Kuhn–Tucker (KKT) analysis.

Multiple antenna systems can be used to increase system reliability or to increase system capacity. Initially, space-time codes were designed to achieve one of these two types of gain. Recently, though, a tradeoff between these two system resources has been characterized by the diversity-multiplexing tradeoff. Achieving this optimal performance frontier requires proper coding. For diversity optimality, the signal transmitted from each antenna must redundantly describe the message bits. This redundancy has been quantified by the rate of a space-time code, which relates space-time codebook size to constituent single-input-single-output (SISO) constellation size. Achievable diversity has also been shown to decrease with increasing rates, which establishes the diversity-rate tradeoff. In this work, we consider a generalized notion of the rate of the space-time code, which we refer to as the code rate Rc, and the associated diversity-code rate tradeoff. We then generalize the diversity-multiplexing and diversity-code rate tradeoffs and find that a new diversity-multiplexing tradeoff exists as a function of the code rate.

Recently, a full rate orthogonal space-time block code achieving full diversity while preserving low decoding complexity with very limited feedback was proposed. Based on a feedback of only p-1 bits, these codes exhibit a higher coding gain as well. In this work, we propose a low complexity, though close to optimal, feedback selection scheme. Furthermore, we analyze the performance of these codes with arbitrary number of transmit and receive antennas. We show that with this feedback based codes full diversity of nTnRPis obtained. Finally, we provide closed form expressions for the ergodic and outage mutual information as well as error rates.

The performance of multiuser MIMO systems can be significantly increased by channel aware scheduling and signal processing at the transmitters based on channel state information. In the multiple-antenna uplink multi-carrier scenario, the base station decides centrally on the optimal signal processing and spectral power allocation as well as scheduling. An interesting challenge is the reduction of the overhead in order to inform the mobiles about their transmit strategies. In this work, we propose to reduce the feedback by chunk processing and quantization. We maximize the weighted sum rate of a MIMO OFDM MAC under individual power constraints and chunk size constraints. An efficient iterative algorithm is developed and convergence proved. The feedback overhead as a function of the chunk size is considered in the rate computation and the optimal chunk size is determined by numerical simulations for various channel models. Finally, the issues of finite modulation and coding schemes as well as quantization of the preceding matrices are addressed.

Current generation wireless systems employ high frequency reuse and shrinking cell sizes. Thus, there has been significant recent attention on the analysis of interference limited systems). We consider single input single output (SISO) broadcast (BC) with intercell interference. We allow the received powers from each source of interference to be different For example, for the two interferer case, a user receives average power c1> 0 from interferer 1 and c2> 0 from interferer 2 where c1and c2need not be equal. We characterize the cumulative distribution function of the resulting signal to interference ratio (SIR) which is a ratio of weighted exponential random variables. It is thus a generalization of the F-distribution which is a scaled ratio of equally weighted exponential random variables. Surprisingly, there is no simple closed form expression for the resulting cdf in the literature. We present a nontrivial calculation that yields a simple, closed form expression for the cumulative distribution function (cdf) of the SIR. We show that this function is a Schur-concave function of the vector of average received powers from the various interferers. Furthermore, we derive a simple closed form expression for the cdf of the SINR. Again, we find that this function is Schur-concave in the average received powers. As a result we conclude that for any average transmit, receive, and thermal noise powers, the probability of achieving any SINR is highest when all interference power originates from a single interferer and lowest when the power is divided equally among the interferers. Opportunistic scheduling (OS) can be an effective tool to mitigate interference. For high signal and interference transmit power, the SINR is well approximated by the SIR. We analyze the scaling of the SIR using OS as the number of users grows for an arbitrary number of interferers. For J received interference powers {cj}j=1j, the SIR is asymptotically inversely proportional to the geometric mean, (Pij=1jcj)1/j.

We study the performance of a communication link with a single-antenna transmitter and a single-antenna receiver in the presence of interferers. This is the building block of wireless systems like sensor networks or multi-cell downlink transmission networks. In more details, we analyze the impact of the location of the interferers on the outage probability of the one-to-one communication link corrupted by the interferers. In order to guarantee a fair comparison, the received average interference power level is kept constant for all scenarios. Conventionally, it is often assumed that the interferers are for simplicity located on a unit circle around the receiver. It turns out that this is a very pessimistic approach. More realistically, the interferers are distributed arbitrarily around the receiver with some interferers being closer to the receiver and some further away. Using majorization theory, we show that the outage probability is a Schur-concave function with respect to the interfererspsila location. This result basically says that having the interferers more spread out within the cell provides lower outages.

This paper presents a practical algorithm for antenna selection in multiple-input multiple-output wireless communication systems employing space-time block codes (STBC). It first shows that maximizing the channel Frobenius norm helps maximize the mutual information for both orthogonal STBC and quasi-orthogonal STBC. However, the computational complexity for finding the optimal antenna subset grows exponentially with the number of antennas. This paper identifies that the channel Frobenius norm maximization problem can be formulated as a quadratically constrained quadratic programming (QCQP) problem. Then, despite the fact that the problem is non-convex, a semidefinite relaxation of QCQP enables the problem to be solved approximately by semidefinite programming in polynomial time. Simulation results indicate that the loss of semidefinite relaxation is negligible. It is also shown that although the combination of STBC and antenna selection is not always beneficial, it is a robust transmission strategy in the high SNR regime when only imperfect channel information is available.

In this paper, we study a wireless multiple-input multiple-output system in a Rayleigh flat-fading environment with correlation among the transmit antennas. We assume that the receiver has perfect CSI and the transmitter only knows the correlation matrix. The transmitter employs a quasi-orthogonal space-time block code in combination with a linear precoder; the receiver uses a linear MMSE detector. We analyze the optimal transmit precoding strategy that minimizes the average sum MSE at the receiver. We show that, as expected, the optimal precoding directions coincide with the eigenvectors of the transmit correlation matrix. The optimal power allocation, however, only supports at most 2 directions at all SNRs independent of the number of transmit antennas, which correspond to the 2 largest eigenvalues of the transmit correlation matrix. We characterize this optimal power allocation by the necessary and sufficient optimality conditions. At high SNRs, the optimal allocation approaches equal power on the two supported modes. At low SNRs, the weaker mode is dropped and the precoding matrix becomes single-mode beamforming. We provide a closed-form expression characterizing this low-SNR range. Numerical simulations confirm our theoretical analysis.

Adaptive transmission techniques including transmit beamforming, preceding, and opportunistic scheduling offer high spectral efficiency when channel state information at the transmitter (CSIT) is accurate, but suffer performance loss when the CSIT quality is poor. Diversity transmission techniques such as space-time coding and frequency interleaving, in contrast, are capable of capturing spatial and spectral diversity without CSIT, hence can provide good performance when CSIT degradation is severe. Between a pair of adaptive and diversity techniques, there exists a switching point in terms of the CSIT-quality; a CSIT- quality higher than this point favors the adaptive technique, but a lower CSIT-quality prefers the diversity one. This paper analyzes several adaptive and diversity schemes for a multiuser multiple-input single-output (MISO) system. Comparative performance in terms of the outage capacity is studied and the CSIT-quality switching points between adaptive and diversity schemes are analyzed. Results are supportive of adaptive transmissions for mobile applications, such as in the downlink of an orthogonal frequency division multiple access (OFDMA) system.

Recently, the capacity region of the MIMO broadcast channel (BC) was completely characterized and duality between MIMO multiple access channel (MAC) and MIMO BC with perfect channel state information (CSI) at transmitter and receiver was established. In this work, we propose a MIMO BC approach in which only information about the channel norm is available at the base and hence no dirty paper precoding (DPC) can be applied. However, a certain set of individual performances in terms of MSE or zero-outage rates can be guaranteed at any time by applying an orthogonal space time block code (OSTBC). The guaranteed MSE region without superposition coding is characterized in closed form and the impact of diversity, fading statistics, and number of transmit antennas is analyzed. The guaranteed MSE region with superposition coding is also studied. Finally, the guaranteed sum MSE is briefly discussed.

If a channel fades fast and the feedback rate of a wireless communication system is low, exploiting long-term channel statistics at the transmitter is more often practical than exploiting instantaneous channel state information. Statistical adaptive modulation scheme based on tap correlation information at the transmitter assuming an orthogonal frequency division multiplexing system with fast mobiles has been proposed. The proposed scheme improves the system performance compared with uniform bit loading scheme. It has been shown that at low SNR, statistical adaptive modulation applied to a channel with high tap correlation results in better performance than that applied to a channel without tap correlation.

Transmit channel side information (CSIT) can significantly increase MIMO wireless capacity. Due to delay in acquiring this information, however, the time-selective fading wireless channel often induces incomplete, or partial, CSIT. In this paper, we first construct a dynamic CSIT model that takes into account channel temporal variation. It does so by using a potentially outdated channel measurement and the channel statistics, including the mean, covariance, and temporal correlation. The dynamic CSIT model consists of an effective channel mean and an effective channel covariance, derived as a channel estimate and its error covariance. Both parameters are functions of the temporal correlation factor, which indicates the CSIT quality. Depending on this quality, the model covers smoothly from perfect to statistical CSIT. We then summarize and further analyze the capacity gains and the optimal input with dynamic CSIT, asymptotically at low and high SNRs. At low SNRs, dynamic CSIT often multiplicatively increases the capacity for all multi-input systems. The optimal input is typically simple single-mode beamforming. At high SNRs, for systems with equal or fewer transmit than receive antennas, it is well-known that the capacity gain diminishes to zero because of equi-power optimal input. With more transmit than receive antennas, however, the capacity gain is additive. The optimal input then is highly dependent on the CSIT. In contrast to equi-power, it can drop modes for channels with a strong mean or strongly correlated transmit antennas. For such mode-dropping at high SNRs in special cases, simple conditions on the channel K factor or the transmit covariance condition number are subsequently quantified. Next, using a convex optimization program, we study the MIMO capacity with dynamic CSIT non-asymptotically. Particularly, we numerically analyze effects on the capacity of the CSIT quality, the relative number of transmit and receive antennas, and the channel K factor. For example, the capacity gain based on dynamic CSIT is more sensitive to the CSIT quality at higher qualities. The program also helps to evaluate a simple, analytical capacity lower-bound based on the Jensen optimal input. The bound is tight at all SNRs for systems with equal or fewer transmit than receive antennas, and at low SNRs for others.

Space-time code (STC) designs classically rely on the assumption of independent and identically distributed (i.i.d.) Rayleigh channels. However, poor scattering conditions may have detrimental effects on the performance of STCs. In this letter, we derive code-design criteria leading to robust STCs in a large variety of slow-fading propagation conditions. No channel knowledge is assumed at the transmitter. Codes satisfying these criteria are shown to perform much better on real-world channels than codes designed only for i.i.d. channels. As examples, the robustness of various spatial multiplexing schemes, linear dispersion codes, and space-time trellis codes is discussed based on those criteria

In closed loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel-statistics-based CSI-Tx requires a much smaller overhead, and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. We focus on a channel environment in which spatial and tap correlation are present. We propose a channel model for the case such that spatial and tap correlation can be separated, and show that this case channel correlation decreases the ergodic capacity of a MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial- and tap-correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlation is investigated.

In closed-loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel statistics-based CSI-Tx requires a much smaller overhead and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) system. We focus on a channel environment in which spatial and tap correlations are present. We propose a channel model for the case that spatial and tap correlations can be separated and show that in this case channel correlation decreases the ergodic capacity of an MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation-based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial and tap correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlations is investigated.

We consider a dense fading multi-user network with multiple active multi-antenna source-destination pair terminals communicating simultaneously through a large common set of K multi-antenna relay terminals in the full spatial multiplexing mode. We use Shannon-theoretic tools to analyze the tradeoff between energy efficiency and spectral efficiency (known as the power-bandwidth tradeoff) in meaningful asymptotic regimes of signal-to-noise ratio (SNR) and network size. We design linear distributed multi-antenna relay beamforming (LDMRB) schemes that exploit the spatial signature of multi-user interference and characterize their power-bandwidth tradeoff under a system-wide power constraint on source and relay transmissions. The impact of multiple users, multiple relays and multiple antennas on the key performance measures of the high and low SNR regimes is investigated in order to shed new light on the possible reduction in power and bandwidth requirements through the usage of such practical relay cooperation techniques. Our results indicate that point-to-point coded multi-user networks supported by distributed relay beamforming techniques yield enhanced energy efficiency and spectral efficiency, and with appropriate signaling and sufficient antenna degrees of freedom, can achieve asymptotically optimal power-bandwidth tradeoff with the best possible (i.e., as in the cutset bound) energy scaling of K-1and the best possible spectral efficiency slope at any SNR for large number of relay terminals. Furthermore, our results help to identify the role of interference cancellation capability at the relay terminals on realizing the optimal power- bandwidth tradeoff; and show how relaying schemes that do not attempt to mitigate multi-user interference, despite their optimal capacity scaling performance, could yield a poor power- bandwidth tradeoff.

The practical challenge of capacity-achieving forward error-correcting codes (e.g., space-time turbo codes) is overcoming the tremendous complexity associated by their optimal joint maximum-likelihood (ML) decoding. For this reason, iterative soft decoding has been studied to approach the optimal ML decoding performance at affordable complexity. In multiple-input multiple-output (MIMO) channels, a judicious decoding strategy consists of two stages: 1) estimate the soft bits using list version of sphere decoding or its variants, and 2) update the soft bits through iterative soft decoding. A promising MIMO decoder is required to produce reliable soft-bit estimates at the first stage before iterative soft decoding is performed. In this paper, we focus on the overloaded (or fat) MIMO antenna systems where the number of receive antennas is less than the number of signals multiplexed in the spatial domain. In this scenario, the original form of sphere decoding is inherently not applicable and our aim is to generalize sphere decoding geometrically to cope with overloaded detection. The so-called slab-sphere decoding (SSD) proposed guarantees to obtain exact-ML hard detection while reducing complexity greatly. With the list-version of SSD, (his paper proposes an efficient MIMO soft decoder, which can generate reliable soft-bit estimates at affordable complexity as inputs for iterative soft decoding for promising performance. A case study in the IEEE 802.16 settings is carried out for performance evaluation

The achievable average sum rate of an OFDMA uplink with multiuser adaptation based on the channel statistics information is investigated in this paper. Multiuser adaptation using channel mean and tap correlation simultaneously is shown to offer large gains in spectral efficiency compared to both uniform subcarrier and power allocation and multiuser adaptation exploiting channel mean information only. Multiuser adaptation efficiently captures multiuser diversity with limited feedback. The impacts of the Ricean K-factor, the magnitude of tap correlation and the number of simultaneously scheduled users per OFDM symbol on the average sum rate are also investigated

In this paper we study the downlink spectral efficiency of a wireless network using orthogonal frequency division multiple access (OFDMA), multiple input multiple output (MIMO) antenna systems and opportunistic scheduling (OS) techniques. The main purpose of the study is to understand how these techniques interact and influence the spectral efficiency of the network for different antenna configurations and scheduling policies given the coherence bandwidth of the channel and mobile speed. We will use the point-to-point link Shannon outage capacity as the underlying metric for evaluating the overall throughput of the network. The results illustrate the relationships between the different techniques.

Recently, there has been a great deal of interest on the performance of MIMO wireless systems as the MIMO fading channel offers an increase in capacity and reliability over that of a SISO channel. When channel state information is not known at the transmitter, the level of performance obtained depends on the degree of cooperation between the transmit antennas. With no cooperation between the antennas, horizontally coded spatial multiplexing is diversity suboptimal since each message bit is encoded and transmitted by only one antenna. An optimal scheme, on the other hand, codes message bits across all transmit antennas. This work generalizes and quantifies the level of cooperation between transmit antennas with the cooperation parameter Rcand then finds upper and lower bounds for the achievable data rates for such a system using a scaled identity transmit covariance matrix. These bounds are found to be tight for certain values of Rcand the data rate Rt. Finally, these bounds are useful in computing the outage probability and diversity order of partially cooperative MIMO systems when channel state information is not known at the transmitter

Sum capacity optimal signatures in synchronous code-division multiple-access (CDMA) systems are functions of the codebook length as well as the number of active users. A new signature set must be assigned every time the number of active users changes. This correspondence considers signature sets that are less sensitive to changes in the number of active users. Equiangular signature sequences are proven to solve a certain max-min signal-to-interference-plus-noise problem, which results from their interference invariance. Unions of orthonormal bases have subsets that come close to satisfying the Welch bound. Bounds on the maximum number of bases with minimum maximum correlation are derived and a new construction algorithm is provided. Connections are made between these signature design problems, Grassmannian line packing, frame theory, and algebraic geometry

The use of multiple antennas at both ends of a wireless link, popularly known as multiple-input multiple-output (MIMO) wireless, has been shown to offer significant improvements in spectral efficiency and link reliability through spatial multiplexing and space-time coding, respectively. This paper demonstrates that similar performance gains can be obtained in wireless relay networks employing terminals with MIMO capability. We consider a setup where a designated source terminal communicates with a designated destination terminal, both equipped with M antennas, assisted by K single-antenna or multiple-antenna relay terminals using a half-duplex protocol. Assuming perfect channel state information (CSI) at the destination and the relay terminals and no CSI at the source, we show that the corresponding network capacity scales as C = (M/2) log(K) + O(1) for fixed M, arbitrary (but fixed) number of (transmit and receive) antennas N at each of the relay terminals, and K rarr infin. We propose a protocol that assigns each relay terminal to one of the multiplexed data streams forwarded in a "doubly coherent" fashion (through matched filtering) to the destination terminal. It is shown that this protocol achieves the cut-set upper bound on network capacity for fixed M and K rarr infin (up to an O(1)-term) by employing independent stream decoding at the destination terminal. Our protocol performs inter-stream interference cancellation in a completely decentralized fashion, thereby orthogonalizing the effective MIMO channel between source and destination terminals. Finally, we discuss the case where the relay terminals do not have CSI and show that simple amplify-and-forward relaying, asymptotically in K, for fixed M and fixed N ges 1, turns the relay network into a point-to-point MIMO link with high-SNR capacity C = (M/2) log(SNR) + O(1), demonstrating that the use of relays as active scatterers can recover spatial multiplexing gain in poor scattering environments

A critical factor in the deployment of multiple-input multiple-output (MIMO) systems is the cost of multiple analog transmit/receive chains. This problem can be mitigated by antenna subset selection at the transmitter/receiver. With antenna selection, a small number of analog chains are multiplexed between a much larger number of transmit/receive antenna elements. In this paper, we present a low complexity approach to receive antenna selection for capacity maximization, based on the theory of convex optimization. We show via extensive Monte-Carlo simulations that the proposed algorithm provides performance very close to that of optimal selection based on exhaustive search. We also, extend this approach to receive antenna selection for the JMMSE and OSIC V-BLAST architectures

In this paper, we propose a greedy algorithm based on a combined space time (ST) code and multimode beamformer (a generalized space time code) to mitigate the effect of fading and interference in a multi-cell system. This is a competitive scheme in which each user acts selfishly to minimize the error probability to its own receiver until an equilibrium is reached. We prove the existence of a Nash equilibrium and find the conditions under which the algorithm converges to this equilibrium. Finally, we demonstrate the performance of the algorithm by numerical simulations

A linear precoder for MIMO channels exploiting both the channel mean and transmit correlation has been shown to improve performance of an orthogonal space-time coded system (Vu, M. and Paulraj, A., Proc. IEEE Vehicular Tech. Conf., 2004). We extend the precoder design to systems with non-orthogonal space-time code, and provide asymptotic analysis at high K factor. The precoder is designed by minimizing the Chernoff bound on the pairwise error probability. While a linear precoder can be viewed as a multi-mode beamformer, it converges to a single beam as the K factor increases. A design criterion based on the minimum codeword distance and a new criterion based on the average codeword distance are considered. Numerical simulations using quasi-orthogonal STBC give examples of the performance gain that can be achieved with these designs.

MIMO wireless systems have been a focus of research for several years, mainly because of the promise of increased channel capacity, extended range, and increased reliability. An aspect of this ongoing research has been concerned with transmit precoding given partial information of the channel. This work focuses on designing a transmit covariance to minimize the probability of outage for a given target data rate over a fading MIMO channel whose distribution is known to the transmitter. This problem is addressed by formulating a convex problem via a heuristic relaxation. Structure of the problem is utilized to simplify the numerical implementation. Finally, the performance of this technique relative to other simpler techniques is considered, therefore showing the utility of this computational technique in evaluating other heuristics.

The impact of tap correlation on the achievable average sum rate of an OFDMA uplink is investigated. Tap correlation between channel taps was showed to reduce the average sum rate of an OFDMA uplink. However, if available subcarriers and power are allocated to multiusers based on their tap correlation information, a hefty portion of inherent multiuser diversity can be exploited in a cost effective manner leading to substantial improvement in spectral efficiency compared with uniform subcarrier and power allocation. The performance gain of such statistical adaptation is further investigated as a function of the number of simultaneously scheduled users per OFDM symbol.

We study performance tradeoffs for joint diversity enhancement and interference mitigation in multi-cell networks with multiple antennas at the transmitter. Our transmitter combines a space time coding block followed by a multimode beamformer. We assume that the transmitter knows the channel covariance for its own and the interfered user. The coding techniques maximize link performance via diversity gain for its own user while constraining the interference power to the interfered (or other) user. We examine strategies for choosing this interference constraint based on greedy or co-operative methods for a symmetric two cell scenario where each link interferes with the other. In the greedy algorithm, each user selfishly maximizes diversity to its own user without regard to the interference it generates to the other user. Both users account for the incoming interference and they eventually iteratively reach the Nash equilibrium (NE). In the co-operative algorithm, each user balances the diversity to its own user but co-operates by limiting the amount of interference to the other user. We show that in the co-operative case, it is possible to find Pareto dominant solutions where the users either maintain or improve their symbol error rate performance

In this paper, we propose a transmitter based scheme to simultaneously mitigate fading to a desired receiver and co-channel interference to an interferee. We focus on downlink transmission at the base station with multiple antennas at transmit and a single receiver at the intended and interferee receivers. We show how appropriate pre-coding and space-time coding can be combined to maximize link performance subject to a specified degree of co-channel interference suppression and assuming a limited amount of information at the transmitter. The resulting solution is compared to transmit beamforming and demonstrates performance improvements due to the additional transmit diversity extracted. In addition, we propose a suboptimal but low complexity implementation of the technique and a modification of the technique to account for errors in the parameters used by the transmitter.

Multiple-input multiple-output (MIMO) wireless communication systems can offer high data rates through spatial multiplexing or substantial diversity using transmit diversity. In this letter, switching between spatial multiplexing and transmit diversity is proposed as a simple way to improve the diversity performance of spatial multiplexing. In the proposed approach, for a fixed rate, either multiplexing or diversity is chosen based on the instantaneous channel state and the decision is conveyed to the transmitter via a low-rate feedback channel. The minimum Euclidean distance at the receiver is computed for spatial multiplexing and transmit diversity and is used to derive the selection criterion. Additionally, the Demmel condition number of the matrix channel is shown to provide a sufficient condition for multiplexing to outperform diversity. Monte Carlo simulations demonstrate improvement over either multiplexing or diversity individually in terms of bit error rate.

This paper highlights the impact of channel correlations on the capacity and performance of MIMO communications, with a focus on the so-called diagonal correlations. Based on this analysis, the limitations of simplified mathematical representations, such as the Kronecker or the diagonal-decorrelation models, are pointed out. Finally, the correlation properties of popular geometry-based statistical models are studied in order to analyze whether the correlation structure of these models can be adequately represented by simplified mathematical models, as well as to quantify the errors introduced by these simplifications. With respect to channel correlations, neither the Kronecker nor the diagonal-decorrelation assumptions are good representations of the correlation structure of the investigated geometry-based statistical models. When comparing capacity and symbol error probability results, it is found that the diagonal-decorrelation model may yield significant errors on both considered metrics. The Kronecker model generally yields errors less than one order of magnitude on the symbol error rate, but relative errors on ergodic or outage capacity may be more significant.

We use field trial results obtained from a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) wireless system with two transmitter and three receiver antennas (2/spl times/3), to first validate the properties of the transmit correlation matrix in a macro-cellular environment. We find that approximately 20% of the locations have well-defined transmit correlation matrices. Furthermore, the eigenvectors of the transmit correlation matrix vary slowly over distance with 60% of the locations having eigenvector variation of less than 1 dB over a distance of 20 m. Next, we quantify the performance of the optimal statistical linear precoding (OSLP) , and statistical one-dimensional (1-D) eigenbeamforming (SEB) based on transmit correlation matrices, and the 1-D eigenbeamforming (EB)-based on perfect channel knowledge at the transmitter. We find that the OSLP and SEB schemes obtain array gain over the Alamouti scheme at lower signal-to-noise ratio (SNR) with a median gain of 2.0 (1.5) dB at the 1.0-(3.5) km cell-radii. However, the SEB scheme (unlike the OSLP scheme) looses diversity order at higher SNR that leads to a performance loss. The EB scheme provides the best performance over the Alamouti scheme, at the expense of increased feedback requirements.

The paper considers a receiver design for space-time block coded MIMO-OFDM transmission over frequency selective time-variant channels. The receiver employs the expectation-maximization (EM) algorithm for joint channel and data recovery. It makes collective use of the data and channel constraints that characterize the communication problem. The data constraints include pilots, the finite alphabet constraint, and space-time block coding. The channel constraints include the finite delay spread and frequency and time correlation. The receiver employs an EM-based Kalman filter for channel estimation. The receiver is able to recover the channel (which varies from one space-time block to the next) and the data with no latency and to reduce the number of pilots needed. Simulations show that the receiver outperforms other least-squares based iterative receivers.

We study the impact of space-time-frequency processing techniques on the physical layer performance of an orthogonal frequency division multiplexing (OFDM) based wireless LAN (IEEE 802.11a/g). A space frequency code (SFC) with two different soft-input soft-output multiple antenna receivers is compared with an orthogonal space time block code (OSTBC) and a single antenna system. We find that the multiple antenna schemes outperform the single antenna scheme as expected with the OSTBC-OFDM scheme providing a diversity improvement and the SFC-OFDM scheme simultaneously improving the diversity and the achievable rate of the system. Throughput curves are used to benchmark the performance of the schemes for specific packet error rates (PERs) and demonstrate the value of switching between architectures/multi-antenna schemes in practical systems.

We propose to apply a technique called time-reversal to UWB communications. In time-reversal a signal is precoded such that it focuses both in time and in space at a particular receiver. Spatial focusing reduces interference to other co-existing systems. Due to temporal focusing, the received power is concentrated within a few taps and the task of equalizer design becomes much simpler than without focusing. Furthermore, temporal focusing allows a large increase in transmission rate compared to schemes that let the impulse response ring out before the next symbol is sent. Our paper introduces time-reversal, investigates the benefit of temporal focusing, and examines the performance of an MMSE-TR equalizer in an UWB channel.

We investigate the capacity behavior of an OFDM wireless link for the frequency selective MIMO channel with correlated paths. The derivation is based on a particular channel model that characterizes path correlation as well as spatial correlation. As in the case of spatial correlation, path correlation can reduce capacity. If there is no channel knowledge at the transmitter, the capacity reduction of an OFDM based system due to path correlation can be explained in terms of the effective SNR at each tone. With spatial and path correlation information at the transmitter, we derive the optimal space-frequency precoder at every tone by numerical optimization techniques. We propose a sub-optimal precoding scheme with lower complexity which leads to a tight lower bound of the capacity of the OFDM system.

The paper discusses antenna subset selection in MIMO wireless systems. The subsets of transmit and receive antennas are selected so as to maximise the channel capacity. First of all, we establish the relationship between the multiplexing gain and the diversity gain achievable with adaptive antenna subset selection. Second, we indicate a selection rule that allows a full diversity advantage to be achieved with a reduced computational effort, by decoupling the combined transmit/receive selection into the separate selection of transmit/receive subsets. Finally, we study the performance of practical systems with antenna selection in the context of high throughput MIMO-OFDM WLAN.

We study a space-time precoding technique for MISO wireless systems by employing a linear prefilter at each transmit antenna. The channel is Rician fading, where the mean and variance of the propagation paths are known to the transmitter. This model includes the Rayleigh fading channels as special cases. We use channel capacity as the optimizing criterion for the prefilter design. This criterion provides a unified design of the prefilters for both Rician and Rayleigh fading channels. The optimum prefilters are functions of the channel mean and variance. The solution ranges from beamforming for Rician channels with high K-factor, to unitary diversity for Rayleigh fading cases, where delay diversity is an example. The MMSE equalizer is then used to detect the signal at the receiver. Analysis of bounds on error rate performance and numerical simulations for 4QAM input signals show significant diversity gains and array gains. The result also illustrates that having partial channel knowledge at the transmitter can strongly enhance the system performance.

Space-time codes designs commonly rely on the assumption of independent and identically distributed Rayleigh channels. However it has been shown that poor scattering conditions can have detrimental effects on the performance of space-time codes. In this communication, we derive a code design criterion leading to robust space-time codes in the presence of a large variety of propagation conditions. No channel knowledge is assumed at the transmitter. Codes satisfying this criterion are shown to perform much better on real-world channels than codes only designed for iid channels. As an example, new Spatial Multiplexing schemes and Linear Dispersion Codes are derived based on this criterion.

Space-time codes designs commonly rely on the assumption of a high SNR. In this communication, we investigate the impact of this assumption when the channel is correlated. Therefore, we discuss the impact of transmit and receive correlations on the performance of space-time codes as a function of the SNR and the diversity achieved by the codes on independent and identically distributed channels. Full diversity codes are shown not to interact with the channel at high SNRs while at realistic SNRs, interactions occur and affect the coding gain. For non-full diversity codes, interactions with the channel occur whatever the SNR. At realistic SNRs, every space-time code interacts with the channel. While it might be reasonable on independent and identically distributed channels, we show that on correlated channels, the 'high SNR' assumption is totally unrealistic and may lead to bad code designs.

The optimum transmission scheme that maximizes ergodic capacity in a K/spl rarr//spl infin/ regime for 2/spl times/1 MISO systems is studied when the channel knowledge at the transmitter is characterized by a known gain imbalance and a known PDF of the phase shift between antennas. Such a channel scenario can arise in a forward link at the base station when there is a single direct path propagation. We show that the optimum transmit solution is beam-forming on the mean value of the phase shift with unequal power input to the antennas. When the phase is completely unknown, the solution reduces to a single antenna transmission.

High data rate wireless communications, nearing 1 Gb/s transmission rates, is of interest in emerging wireless local area networks and home audio/visual networks. Designing very high speed wireless links that offer good quality-of-service and range capability in non-line-of-sight (NLOS) environments constitutes a significant research and engineering challenge. Ignoring fading in NLOS environments, we can, in principle, meet the 1 Gb/s data rate requirement with a single-transmit single-receive antenna wireless system if the product of bandwidth (measured in hertz) and spectral efficiency (measured in bits per second per hertz) is equal to 10/sup 9/. A variety of cost, technology and regulatory constraints make such a brute force solution unattractive, if not impossible. The use of multiple antennas at transmitter and receiver, popularly known as multiple-input multiple-output (MIMO) wireless, is an emerging cost-effective technology that offers substantial leverages in making 1 Gb/s wireless links a reality. The paper provides an overview of MIMO wireless technology covering channel models, performance limits, coding, and transceiver design.

In this letter, we propose an interference-suppressing RAKE receiver for the code division multiple-access (CDMA) downlink. In the downlink, the received signal has a special structure that makes it possible for a RAKE receiver (which is a simple low-complexity linear receiver) with appropriately chosen weights to suppress interference efficiently. While there have been a few other interference-suppressing RAKE receivers proposed recently, our design is based on a different motivation, and we show that our approach significantly outperforms them especially when the number of active users in the cell is not large.

This paper describes a multidimensional model of the fixed wireless propagation channel, which is well suited to system-level simulations. The proposed method yields realistic predictions of various channel characteristic parameters as a function of the range and antenna beamwidths, in agreement with experimentally observed results. The originality of the approach is that the power-delay profile for omnidirectional antennas at the edge of the cell is used to predict the time-varying channel over the whole cell for any antenna beamwidth. The method is based on a set of spatially distributed scatterers, which can be scaled to any range within the cell. The time-varying channel impulse response is then calculated as the combination of all scattered contributions by means of a ray approximation. The multidimensionality of the channel model is explored through predictions of signal statistics, level-crossing rate, delay-spread and angle-spread. In contrast to most existing models, the impact of range and antenna beamwidth is clearly addressed and found to be close to experimentally observed behaviors.

Abstract We study the optimum transmission scheme that maximizes ergodic capacity of a 2 × 1 multiple‐input single‐output (MISO) system, when the channel knowledge at the transmitter is characterized by a known gain ratio and a known probability density function (PDF) of the phase shift between antennas. Such a channel scenario can arise in a forward link at the base station when there is a single direct path propagation. We show that the optimum transmit solution is beamforming on the mean value of the phase shift with unequal power input to the antennas. When the phase is completely unknown, the solution reduces to a single antenna transmission. Copyright © 2004 John Wiley & Sons, Ltd.

We propose and analyze a new technique for improving RAKE receivers for DS-CDMA systems that eliminates the loss due to incorrect finger assignment. Such loss occurs due to errors caused by the searcher in estimating the average power of multipaths. Our technique uses a mobile location indexed database of multipath delays and average powers obtained error-free through offline techniques. During a mobile call, the mobile location is used to look up the database and obtain error-free finger assignment information. We analyze the improvement due to such a "genie"-aided scheme on the performance of the RAKE receiver in terms of the SNR required to achieve a target BER and in terms of the system user capacity under a 4-path Rayleigh fading scenario.

Codebooks constructed from Welch bound equality (WBE) sequences have been show to be optimal in terms of sum capacity in synchronous CDMA systems. Unfortunately, these codebooks are a function of the number of active signatures and need to be reassigned as the number of active users changes to maintain optimality. To mitigate the problems caused by the loss of the Welch bound equality property, in this paper we propose a special subclass of WBE sequences for which the interference power experienced by each user depends only on the number of active users and the dimensions of the code. In deference to the relationship with Grassmannian line packing, we refer to this as a Grassmannian signature set. We study the interference properties of this set, comment on the sequence design problem, and illustrate improvements over arbitrary WBE sequence sets via simulation.

Crosstalk is the major source of performance degradation in VDSL. A number of crosstalk cancellation techniques have been proposed to address this. Whilst these schemes lead to large performance increases they also have high run-time complexities, a problem which grows rapidly with the number of lines within a binder. Since the majority of crosstalk typically comes from only a few dominant crosstalkers, it is possible to do partial crosstalk cancellation. We present a low-complexity, partial crosstalk cancellation technique for VDSL based on line selection. We derive the optimal line selection technique, and several low-complexity selection algorithms which give near-optimal performance in most scenarios. These techniques lead to significant reductions in runtime complexity whilst giving similar performance to full crosstalk cancellation.

The use of spatial multiplexing (SM) in multiple-input multiple-output (MIMO) wireless systems promises a linear (in the minimum of the number of transmit and receive antennas) increase in data rate. In practice, the performance of SM depends critically on a variety of channel conditions, including antenna height and spacing, polarization of antennas, and richness of scattering. Transmit correlation has been shown to be detrimental to the performance of SM, since it leads to the existence of preferred spatial directions. In addition, the presence of an ill-conditioned fixed (possibly line-of-sight) component in the channel can severely degrade performance. We present a simple transmit optimization strategy to mitigate partially the impact of unfavorable channel statistics on the performance of SM. The proposed strategy takes the scalar symbol constellation and the channel statistics into account and relies on simple phase-shifting of the multiplexed symbol streams at the transmitter. The phase shifts are chosen such that the cut-off rate of the effective channel (physical channel in combination with finite constellation and ML decoding) is maximized. We find SNR gains of up to 4 dB over the case when no transmit optimization is employed.

Space-frequency coded orthogonal frequency division multiplexing (OFDM) is capable of realizing both spatial and frequency-diversity gains in multipath multiple-input multiple-output (MIMO) fading channels. This naturally leads to the question of variable allocation of the channel's degrees of freedom to multiplexing and diversity transmission modes. In this paper, we provide a systematic method for the design of space-frequency codes with variable multiplexing-diversity tradeoffs. Simulation results illustrate the performance of the proposed codes.

This paper discusses antenna sub-set selection in multiple-input multiple-output wireless systems. The antennas are selected so as to maximize the channel capacity. We present a near-optimal selection algorithm that enables tractable statistical analysis of the selection gain. We show that with antenna selection the capacity is statistically lower bounded by the capacity of the set of parallel independent SIMO channels each with selection diversity. We leverage this result to prove the equivalence in diversity order between the full system (all receive antennas) and the system with antenna selection. Simulations validating analysis and illustrating algorithm performance are also presented.

Previous work on space-frequency coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) has been restricted to idealistic propagation conditions. In this paper, using a broadband MIMO channel model taking into account Ricean K-factor, transmit and receive angle spread, and antenna spacing, we study the impact of the propagation environment on the performance of space-frequency coded MIMO-OFDM. For a given space-frequency code, we quantify the achievable diversity order and coding gain as a function of the propagation parameters. We find that while the presence of spatial receive correlation affects all space-frequency codes equally, spatial fading correlation at the transmit array can result in widely varying performance losses. High-rate space-frequency codes such as spatial multiplexing are typically significantly more affected by transmit correlation than low-rate codes such as space-frequency block codes. We show that in the MIMO Ricean case the presence of frequency-selectivity typically results in improved performance compared to the frequency-flat case.

This paper presents a physical scattering model that predicts multiple-input multiple-output (MIMO) channel characteristics conforming well to experimental observations in macrocells. Our approach is to start with a given single-input single-output power-delay profile (defined for specific range, bandwidth and antenna parameters) and fit a scattering model that characterizes the MIMO channel. From the derived scattering model and antenna array configurations, the MIMO channel is computed using a ray-based method. Simulations of several MIMO channels are shown to exhibit experimentally observed channel correlations, antenna beamwidth effect, range dependency, and frequency selectivity.

This correspondence discusses the problem of the receive antenna subset selection in multiple-element antenna (MEA) transmission systems. The antennas are selected so as to maximize the channel capacity. A set of near-optimal selection algorithms is presented. The first algorithm in particular allows statistical analysis of selection gains. We present tight analytic lower bounds on the outage capacity achievable through antenna selection. Extensive simulations validating analysis and illustrating performance of the selection algorithms are also presented.

OFDM modulation combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the receiver needs accurate channel information. In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem - a structure induced by the data and channel constraints. These constraints include pilots, the cyclic prefix (CP), and the finite alphabet constraints on the data, and sparsity, finite delay spread, and the statistical properties of the channel (time and frequency correlation). Channel identification and equalization is performed optimally and recovery is achieved within the same OFDM symbol using an EM based Kalman filter.

We consider Gaussian multiple-input multiple-output (MIMO) fading channels assuming that the channel is unknown at the transmitter and perfectly known at the receiver. Using results from multivariate statistics, we derive a tight closed-form lower-bound for the ergodic capacity of such channels at any signal-to-noise ratio (SNR). Moreover, we provide an accurate closed-form analytical approximation of ergodic capacity in the high SNR regime. Our analysis incorporates the frequency-selective Rayleigh fading case and/or spatial fading correlation, and allows Important Insights Into optimal (ergodic capacity maximizing) MIMO configurations. Finally, we verify our analytical expressions through comparison with numerical results.

This work proposes an iterative least-/ mean-squares approach to channel identification and equalization in OFDM. This is achieved by exploiting the natural constraints imposed by the channel (sparsity and maximum delay spread) and those imposed by the transmitter (pilots, cyclic prefix, and the finite alphabet constraint). These constraints are used to reduce the number of pilots needed for channel and data recovery and also to perform this task within one packet. The diagonal nature of the OFDM channel makes it possible to perform optimal (nonlinear) mean-square detection of the data.

The performance of space-time block codes is well understood from an average (over the random channel) error point of view. However, inherent to the idea of diversity gain is the issue of reliability, which is better captured through an outage analysis indicating the quality of performance guaranteed with a certain level of reliability. In this paper, we study the outage performance of a simple space-time block code, the Alamouti scheme, in the presence of correlated Rayleigh or Ricean fading. We derive expressions for the cumulative distribution function of the uncoded symbol error rate and verify the accuracy of our analytical expressions through comparison with numerical results. In addition, we introduce a quantitative measure to compare the diversity gain offered by two channels at a given outage rate.

A number of space-time block codes have been proposed for the quasi-static, flat-fading channel with coherent receiver. All of these block codes are linear codes, i.e., the encoded codeword is a linear function of the input scalar symbols. Here we propose new non-linear space-time block codes, i.e., the codewords are non-linear functions of the input scalar symbols. We demonstrate a non-linear code that outperforms the corresponding linear code by 0.6 to 1.2 dB. We draw parallels between optimal non-linear code design and the well-known simplex conjecture for multi-dimensional A WGN codes. Finally we show that for certain non-uniformly distributed input symbols, the optimal signal set cannot be designed with linear modulation and non-linear modulation is essential for optimality. This has applications in the design of space-time trellis codes and concatenated space-time coding schemes.

We present capacity, envelope correlation coefficient, and condition number statistics obtained from 2/spl times/2 multiple-input multiple-output (MIMO) fixed wireless radio channel measurements using dual-polarized antennas. To calculate the capacity, we assume that the transmitter has no knowledge about the channel. The experimental capacity results are compared to the information-theoretic channel capacity obtained from Monte Carlo simulations. Both theoretical results and experimental results show that depending on the temporal K-factor, rank of the constant matrix, envelope correlation coefficients of the variable matrix, and cross-polarization discrimination, the capacity can assume range of values for a given average SNR. The envelope correlation coefficients were found to be less than 0.42 for the 90% of cases. The condition numbers were found to be less than 10 for the majority of cases.

Spatial multiplexing is a signaling strategy for achieving high spectral efficiencies in communication links that employ multiple transmit and multiple receive antennas. In such systems, it is desirable to use only a subset of the available transmit and/or receive antennas to reduce cost and complexity. We address the problem of optimal antenna subset selection in spatial multiplexing systems when only the second-order statistics of the channel are available. We derive selection criteria for both the maximum likelihood and zero forcing receivers, motivated by minimizing the average symbol error rate. We characterize the antenna selection gain and show that both coding gain and diversity gain is possible. We then use Monte Carlo simulations to validate our analysis.

Multiple input multiple output antenna subset selection is a low cost low complexity technique with the benefits of multiple antennas. This paper addresses the problem of statistical MIMO antenna sub-set selection with space-time coding. The antennas are chosen based on second order channel statistics, the goal being to minimize the average probability of error. We show that the optimal antenna set maximizes the determinant of the covariance of the vectorized channel. The derived selection rule allows simultaneous (joint) selection of optimal transmit and receive antennas. We discuss propagation scenarios in which the selection rule decouples so that joint selection can be carried out by performing transmit selection independent of the receive antennas and vice versa. The selection gain is quantified as the performance improvement due to transmission/reception on the optimal set instead of any other selection. We show the possibility of both coding gain as well as diversity gain. Finally, we support our analysis with simulations.

Space-time coding for the flat fading, quasi-static MIMO wireless channel has received widespread attention. This paper treats space-time code design for frequency selective channels from a single carrier modulation perspective. We present a general framework for analyzing space-time codes for delay spread channels based on PEP analysis. It is shown that as in the flat fading case, diversity gain is driven by the minimum rank of the pairwise codeword difference matrices. Delay spread, however, imposes a block Hankel structure on the codewords which may prevent certain codes designed for the flat fading case from exploiting full spatio-temporal diversity when used over frequency selective channels. We explicitly show this diversity loss for the delay diversity code. We show that a properly generalized delay diversity (GDD) code achieves full diversity over frequency selective channels. Finally we propose an extension to the GDD which fits naturally in a multi-carrier setting.

This paper summarizes our 2/spl times/2 multiple-input multiple-output (MIMO) fixed wireless outdoor propagation measurements at 2.48 GHz conducted in the suburban residential areas of San Jose, California. We report on various channel characteristics such as path loss, Ricean K-factor, cross-polarization-discrimination (XPD) and channel capacity. We present simple models for these characteristics, focusing on excess loss dependency and, derived from that, the variation with distance. Also, we introduce an idea for a generalized MIMO channel model based on these modeled channel characteristics and the correlation properties between them. Path loss results show that blockage due to buildings or foliage causes an excess loss of 35.45 dB compared to free space propagation at a distance of 1 km. The narrowband K-factor distribution matches previously reported results. The XPD of the total received signal varies from -10 to 15 dB at various locations. The K-factor and XPD were found to be very much dependent on excess loss due to blockage conditions at various distances.

This paper deals with the capacity behavior of wireless orthogonal frequency-division multiplexing (OFDM)-based spatial multiplexing systems in broad-band fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver. Introducing a physically motivated multiple-input multiple-output (MIMO) broad-band fading channel model, we study the influence of physical parameters such as the amount of delay spread, cluster angle spread, and total angle spread, and system parameters such as the number of antennas and antenna spacing on ergodic capacity and outage capacity. We find that, in the MIMO case, unlike the single-input single-output (SISO) case, delay spread channels may provide advantages over flat fading channels not only in terms of outage capacity but also in terms of ergodic capacity. Therefore, MIMO delay spread channels will in general provide both higher diversity gain and higher multiplexing gain than MIMO flat fading channels

We present a new model for multiple-input-multiple-output (MIMO) outdoor wireless fading channels and their capacity performance. The proposed model is more general and realistic than the usual independent and identically distributed (i.i.d.) model, and allows us to investigate the behavior of channel capacity as a function of the scattering radii at transmitter and receiver, distance between the transmit and receive arrays, and antenna beamwidths and spacing. We show how the MIMO capacity is governed by spatial fading correlation and the condition number of the channel matrix through specific sets of propagation parameters. The proposed model explains the existence of "pinhole" channels which exhibit low spatial fading correlation at both ends of the link but still have poor rank properties, and hence, low ergodic capacity. In fact, the model suggests the existence of a more general family of channels spanning continuously from full rank i.i.d. to low-rank pinhole cases. We suggest guidelines for predicting high rank (and hence, high ergodic capacity) in MIMO channels, and show that even at long ranges, high channel rank can easily be sustained under mild scattering conditions. Finally, we validate our results by simulations using ray tracing techniques. Connections with basic antenna theory are made.

Multiple-input multiple-output (MIMO) wireless systems employ spatial multiplexing to increase data rate. The performance of spatial multiplexing is highly dependent on channel statistics which in turn depend on antenna spacing and richness of scattering. It has been shown Bolcskei and Paulraj, (see Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, Oct./Nov. 2000) that the presence of transmit correlation can have a detrimental effect on the performance of multi-antenna signaling techniques. We present a novel scheme to (partly) mitigate the performance loss of spatial multiplexing in the presence of highly correlated fading at the transmitter. The adaption to be performed at the transmitter is a form of power allocation and/or relative phase adjustment between the different symbol streams to be multiplexed. We consider the cases of dual-polarized as well as uni-polarized antennas and derive estimates of the uncoded average symbol error rate as a function of channel statistics, power allocation and phase adjustment. We then optimize power allocation and phase adjustment and demonstrate that this form of preprocessing can yield SNR gains of up to 4 dB over the case where no precoding is employed.

A number of space-time codes have recently been proposed for the quasi-static, flat-fading, multiple-antenna wireless channel with coherent receiver. We focus on space-time codes that are linear in the scalar input symbols. We provide design criteria that take into account both the error probability and the channel capacity. We consider the error probability via the union bound instead of the conventional pairwise error probability and provide conditions on unitary codes to minimize the union bound. Then, we provide conditions on linear codes to maximize channel capacity, i.e. capacity-efficient codes. Finally we provide design rules that optimize the error performance of capacity-efficient codes, and demonstrate performance improvements via simulations.

In practice large antenna spacings are needed to achieve high capacity gains in multiple-input multiple-output (MIMO) wireless systems. The use of dual-polarized antennas is a promising cost effective alternative where two spatially separated antennas can be replaced by a single antenna element employing orthogonal polarizations. This paper investigates the performance of spatial multiplexing in MIMO wireless systems with dual-polarized antennas. We compute estimates of the symbol error rate as a function of cross-polarization discrimination (XPD) and spatial fading correlations. Using these estimates, we show that dual-polarized antennas can significantly improve the performance of spatial multiplexing systems. It is demonstrated that improvements in terms of symbol error rate of up to an order of magnitude are possible. We furthermore find that in general for a given SNR there is an optimum XPD for which the symbol error rate is minimum. Finally, we present simulation results and we show that our estimates closely match the numerical results.

Space-time block codes provide maximal diversity advantage over a fading channel. This paper presents a novel technique that provides additional diversity gain by coupling antenna selection with a space-time block code. Specifically, we provide a choice of transmit antenna elements at the transmitter and transmit a space-time code over the optimal antenna pair. We present the optimal selection rule and quantify the improved performance in terms of gain in average SNR. The average SNR gain is calculated as a function of the number of transmit antenna elements and the number of receive antennas. We also investigate the improvement in outage capacity.

Wireless systems with multiple transmit and receive antennas (MIMO systems) provide high capacity due to the plurality of modes available in the channel. Previous code designs for MIMO systems have focused primarily on multiplexed signaling for high data rate or diversity signaling for high link reliability. Based on Ganesan and Stoica (2000) and Hassibi and Hochwald (2000), and using results from frame theory, we present a MIMO space-time code design which bridges the gap between multiplexing and diversity and performs well both in terms of ergodic capacity as well as error-probability. In particular, we demonstrate that designs performing well from an ergodic capacity point of view do not necessarily perform well from an error probability point of view. Simulations illustrate performance of the proposed codes in narrowband MIMO Rayleigh fading channels.

The design of practical coding techniques for the multiple antenna wireless channel is a challenging problem. A number of interesting solutions have been proposed ranging from block codes to trellis codes for the MIMO (multiple input, multiple output) channel. We consider linear block codes for the quasi-static, flat-fading, coherent MIMO channel. A linear code refers to an encoder that is linear with respect to scalar input symbols. We assume maximum likelihood decoding at the receiver. We provide a cohesive framework for analysis of linear codes in terms of a union bound on the conditional probability of symbol error. The error bound is a function of the instantaneous channel realization and does not make any assumptions on channel statistics. We show that the orthogonal block codes proposed by Tarokh, Jafarkhani and Calderbank, (see IEEE Trans. Information Theory, vol.45, no.5, p.1456-67, 1999) achieve the lowest error bound among all unitary codes and are in fact optimal.

The choice of the spatial frequency reuse and the channel plan in multi-cellular wireless systems plays an important role in effectively combating co-channel interference (CCI) and enhancing system capacity. In this paper, we compare the performance of four different interleaved channel and polarization assignment combinations of three spatial frequency reuse schemes in quad-sector cell architecture. The schemes are further compared with the traditional tri-sector cell cluster size N=3. For the tri-sector cell, a 90 degree sector antenna is proposed while a 60 degree one is chosen for the quad-sector cell. The relative beamwidths, from off-the-shelf antenna radiation patterns, are tradeoffs between minimizing CCI and maximizing the sector coverage at the sector boundaries. We demonstrate that (a) the quad-sector architecture has a higher capacity for 90% area coverage than the tri-sector cell. (b) the combination of interleaved channel assignment (ICA) and interleaved polarization assignment (IPA) offered the most enhanced capacity. For a reuse cluster size N=1, capacity enhancement with combined ICA and IPA measured 45% better than without using any assignment. For N=2, this measured 85% while for N=3, it measured 63%. These improvements pertain to cross-polarization discrimination (XPD) of 6 dB. (c) IPA and rotating channel assignment (RCA) in the tri-sector reuse cluster of N=3 are not effective tools for enhancing capacity.

Future wireless systems will employ multiple antennas at both transmitter and receiver to take advantage of large capacity gains. Two competing spatial modulation techniques for such systems are multiplexing, for high spectrum efficiency; and diversity, for high reliability. In this paper we show that the Demmel (1988) condition number of a MIMO (multiple-input multiple-output) channel characterizes its suitability for multiplexed transmission, over diversity transmission, based on a minimum Euclidean distance comparison. We examine the probability of obtaining channels suitable for multiplexing as a function of constellation, rate, and number of antennas, for i.i.d. flat-fading Rayleigh matrix channels.

Future cellular systems will employ spatial multiplexing with multiple antennas at both transmitter and receiver to take advantage of large capacity gains. In such systems it will be desirable to select a subset of available transmit antennas for link initialization, link maintenance, or handoff. In this paper we present a criteria for selecting the optimal antenna subset in terms of minimum error rate, when coherent receivers, either linear or maximum likelihood (ML), are used over a slowly varying channel. For the ML receiver we propose to pick the subset whose output constellation has the largest minimum Euclidean distance. For the linear receiver we propose use of the post-processing SNRs (signal to noise ratios) of the multiplexed streams whereby the antenna subset that induces the largest minimum SNR is chosen. Simulations demonstrate that our selection algorithms also provides diversity advantage thus making subset selection useful over fading channels.

Two outstanding examples of transmit diversity schemes for the multiple-antenna flat-fading channel are space-time block coding (STBC) and space-time trellis coding (STTC). We compare the performance of STBC and STTC in terms of the frame error rate keeping the transmit power, spectral efficiency and number of trellis states fixed. We discover that a simple concatenation of space-time block codes with traditional AWGN (additive white Gaussian noise) trellis codes outperforms some of the best known space-time trellis codes at SNRs (signal to noise ratios) of interest. Our result holds for a small number of trellis states with one or two receive antennas, and is useful for the design and implementation of multiple-antenna wireless systems.

Co-channel interference (CCI) from other reuse cells restricts the channel capacity of cellular communication systems. In fixed wireless access systems, the deployment of directional antennas at the customer premises equipment (CPE) that point towards their base stations suggest a direct and easy method to combat CCI and enhance capacity in a line-of-sight (LOS) propagation scenario. However, in a non-line-of-sight (NLOS) scenario, the effect of using a directional antenna at the CPE depends on the multipath angle of arrival (AOA) distribution of the propagating channel. In this paper, we demonstrate and compare the downlink performance of the directional antenna at the CPE under different AOA conditions. Two multipath channel models are assumed: circular and elliptical scattering models. We also calculate the performance of the adaptive array antenna deployed at the CPE and calculate its beamwidth effect. The capacity performance of the adaptive array antenna is compared with that of the single directional antenna.

We address the problem of designing jointly optimum linear precoder and decoder for a MIMO channel possibly with delay-spread, using a weighted minimum mean-squared error (MMSE) criterion subject to a transmit power constraint. We show that the optimum linear precoder and decoder diagonalize the MIMO channel into eigen subchannels, for any set of error weights. Furthermore, we derive the optimum linear precoder and decoder as functions of the error weights and consider specialized designs based on specific choices of error weights. We show how to obtain: (1) the maximum information rate design; (2) QoS-based design (we show how to achieve any set of relative SNRs across the subchannels); and (3) the (unweighted) MMSE and equal-error design for fixed rate systems.

We present a new model for multiple-input multiple-output (MIMO) outdoor wireless fading channels which is more general and realistic than the usual i.i.d. model. We investigate the channel capacity as a function of parameters such as the local scattering radius at the transmitter and the receiver, the distance between the transmit (TX) and receive (RX) arrays, and the antenna beamwidths and spacing. We point out the existence of "pin-hole" channels which exhibit low fading correlation between antennas but still have poor rank properties and hence low capacity. Finally we show that even at long ranges high channel rank can easily be obtained under mild scattering conditions.

We propose a transmit diversity scheme for frequency selective fading channels using orthogonal frequency division multiplexing (OFDM). The transmit diversity scheme proposed by Alamouti (see IEEE JSAC, vol.16, no.8, p.1451-58, 1998) for flat fading channels is extended to the case when the channel has a delay spread. There is no loss in receive SNR due to the delay spread in the channel. A diversity order of 2N can be achieved by using two transmit and N receive antennas. We discuss several interesting aspects of the approach and compare it with other extensions of the Alamouti scheme for delay spread channels.

We compute the capacity of wireless orthogonal frequency division multiplexing (OFDM)-based spatial multiplexing systems in delay spread environments. Introducing an abstract model to characterize the statistical properties of the space-time channel, we provide a Monte-Carlo method for estimating the capacity cumulative distribution function, expected capacity, and outage capacity for the case where the channel is unknown at the transmitter and perfectly known at the receiver. We study the influence of the propagation environment and system parameters on capacity, and we apply our method to spatial versions of standard channels taken from the GSM recommendations. This allows us to make statements about achievable data rates of OFDM-based spatial multiplexing systems operating in practical broadband propagation environments.

Previous work has shown that the use of multiple antennas in a fading environment results in a linear increase in capacity. This paper examines the capacity of a multiple antenna element array (MEA) in a quasi-static flat fading environment with a rank deficient channel. We assume that the channel is known at the receiver and the existence of a feedback path to the transmitter. For a particular channel realization, we show that the judicious use of fewer transmit antennas when the channel matrix is ill-conditioned can increase system capacity. We develop a criterion for selecting an optimum set of transmit antennas. This selection is optimal in the sense that the capacity of the resulting MEA system is greater than that for any other configuration with the same number of transmit antennas chosen from the original set. The resulting channel is full rank.

We propose a new blind space-time linear multiuser receiver for the CDMA downlink. The structure in the multiple access interference (MAI) for the downlink makes it possible for a receiver to suppress it without first obtaining the matched filter outputs for all the users (which comprise the sufficient statistics for optimum detection of the transmitted symbols); a 2D-RAKE receiver with appropriately chosen taps can suppress MAI reasonably well. Knowledge of all the users' codes is assumed and the taps of the 2D-RAKE receiver are estimated by making use of the subspace structure in the transmitted signal. Our approach does not require training symbols or channel estimation in order to estimate the receiver taps.

Alamouti (see Journal of Selective Communications, vol.16, no.8, p.1451-58, 1998) proposes a two branch transmit diversity scheme for channels without intersymbol interference. With two transmit antennas and one receive antenna the scheme provides second order diversity. In this paper we derive a new method which handles the corresponding case when the channel suffers from intersymbol interference. The intersymbol interference can be caused by partial response modulation and/or delay spread in the propagation channel. As in Alamouti's paper, we show that with two transmit and one receive antenna, the same diversity can be achieved as with one transmit and two receive antennas. This new proposed scheme thus achieves full diversity for channels with intersymbol interference.

Space-time coding for fading channels is a communication technique that realizes the diversity benefits of multiple transmit antennas. Previous work in this area has focused on the narrowband flat fading case where spatial diversity only is available. We investigate the use of space-time coding in OFDM-based broadband systems where both spatial and frequency diversity are available. We consider a strategy which basically consists of coding across OFDM tones and is therefore called space-frequency coding. For a spatial broadband channel model taking into account physical propagation parameters and antenna spacing, we derive the design criteria for space-frequency codes and we show that space-time codes designed to achieve full spatial diversity in the narrowband case will in general not achieve full space-frequency diversity. Specifically, we show that the Alamouti (see IEEE J. Sel. Areas Comm., vol.16, p.1451-58, 1998) scheme across tones fails to exploit frequency diversity. For a given set of propagation parameters and given antenna spacing, we establish the maximum achievable diversity order. Finally, we provide simulation results studying the influence of delay spread, propagation parameters, and antenna spacing on the performance of space-frequency codes.

We consider the problem of linear polyphase blind equalization (BE), i.e. we are interested in equalizing the output of a single-input-multiple-output (SIMO) channel, without observing its input. A previous result by Liu and Dong (see IEEE Trans. on Circuits and Systems, vol.44, no.5, 1997) showed that if the sub-channel polynomials are co-prime in the z-domain, then the equalizer output whiteness is necessary and sufficient for the equalization of a white input. Based on this observation, we propose a simple decorrelation criterion for second-order based BE. Due to its second-order nature, this criterion is insensitive to the distance of the input from Gaussianity, hence it achieves BE even for Gaussian or non-Gaussian inputs. Moreover, unlike other second-order techniques, our approach bypasses channel estimation and computes directly the equalizer. By doing so, it avoids the problem of ill-conditioning due to channel order mismatch which is crucial to other techniques. Combined to its good convergence properties, these characteristics make the proposed technique an attractive option for robust polyphase BE, as evidenced by both our analysis and computer simulation results.

The paper describes the architecture of the Stanford University (SU) TDMA standalone testbed. The testbed was developed to evaluate space-time processing (STP) algorithms for diversity, co-channel interference (CCI) and intersymbol interference (ISI) mitigation, array gain and space-time coding. It operates in both uplink and downlink modes and uses a hybrid (combining a real and simulated) channel environment. A description of transmit and receive schemes implemented on the testbed is presented.

Communicating reliably over the wireless fading channel is a significant challenge. Previous work has focused on exploiting the plurality of antennas available at the basestation for transmit diversity. As the forward channel is not typically known, transmit diversity schemes couple energy into the spatial channel without regard to the interference created towards cochannel users in other cells. To alleviate these problems we present a transmit diversity technique which uses strategically placed sets of antenna arrays and partial channel knowledge to direct multiple beams from different spatial locations to each user. Beamforming on each antenna array is used to achieve lower crosstalk among users while the presence of multiple arrays provides diversity benefit. Analysis of the proposed system using the pairwise error probability is presented along with simulations assuming perfect channel knowledge at the receiver.

This paper describes an adaptive space-time receiver with joint channel-data estimation (JCDE) to combat time-varying (TV) multipath channels in the presence of undesired cochannel interference (CCI). The receiver uses a colored Gaussian metric for sequence detection in order to suppress the CCI. The proposed scheme also uses the knowledge of the transmit filter for improved channel estimation to enhance performance. The algorithm is derived as a quasi-Newton scheme on a chosen cost criterion and is also locally convergent. The performance of this class of interference cancellers is examined through the pairwise error probability (PEP). Through these expressions we gain insight into the properties of the canceller. The effect of channel dynamics and identification mismatch on the PEP is also examined. To reduce implementational complexity, a hybrid delayed-decision feedback and JCDE scheme is also proposed. The performance is illustrated using numerical results in realistic transmission environments.

We propose a novel algorithm for the maximum-likelihood sequence estimation (MLSE) equalizer for the Global System for Mobile Communications (GSM) system. Specifically, we use a parametric model for the channel, along with a modified phase pulse-shaping function of Gaussian minimum shift keying (GMSK) modulation to obtain the modified Viterbi equalizer which we refer to as the parametric channel-Viterbi equalizer (PC-VE). In contrast to the conventional Viterbi equalizer with a finite impulse response (FIR) channel description, the PC-VE avoids the linear approximation error. The PC-VE also has a lower computational complexity if the number of the propagation paths is less than the number of the FIR channel taps multiplied by the number of antennas. The proposed algorithm is applicable to both single and multiantenna receivers. An analytical expression for the BER as a function of the SNR, path delays, and path DOAs has been derived. Some simulation results that illustrate the performance of the proposed algorithm are presented.

The recovery of code-division multiple access (CDMA) information signals in a frequency selective fading channel is a problem of great theoretical and practical interest. This paper addresses the estimation of an optimal (within the class of linear detectors) multi-user CDMA receiver. A novel approach is introduced that enables the estimation of the minimum mean-square error (MMSE) detector in a blind setting. The MMSE detector is obtained through a double subspace projection that exploits the subspace structure associated with both the code of the desired user and the estimated signal subspace of the covariance matrix for the observed signals. The technique allows for interference rejection without requiring the knowledge of the codes for the interferers.

This paper describes a direct equalization approach for channels with some underlying structure. A semi-blind approach is taken here where a small amount of training symbols is available. A family of MMSE equalizers is obtained that includes some prior information about the channel structure. The channel structure assumed in this paper is that the channel vector lies approximately in the subspace of a matrix associated with the samples of the transmit pulse shape. Blind identifiability issues of the structured equalizer are also addressed. Numerical results using experimental indoor channel data indicate that these structured equalisers can achieve bit error rates that are significantly lower than traditional non-blind MMSE equalizers.

This paper describes an adaptive space-time receiver with joint channel and data estimation (JCD) to combat time-varying multipath channels in the presence of undesired co-channel interference (CCI). The receiver uses a colored Gaussian metric in the sequence detection to suppress the CCI. The proposed scheme also uses the knowledge of the transmit filter for improved channel estimation to enhance the performance. We gain insight into the interference suppression scheme through pairwise error-probability analysis. To reduce implementational complexity, a hybrid delayed-decision feedback and JCD scheme is also proposed. The performance is illustrated using numerical results in realistic transmission environments.

This paper addresses the problem of multi-user detection in the context of cellular CDMA and frequency selective channels. Structures and algorithms are proposed for the receiver design, that combat both strong multiple access interference (MAI) and inter-chip interference (ICI) in possibly asynchronous networks. Two novel receiver structures are proposed. The first one allows for the estimation of the channel characteristics for one or multiple users before signal detection. The second approach is simpler and directly acquires the coefficients of several multi-user detectors with multiple delays. These methods are blind in the sense that no pilot sequences are used to estimate the coefficients of the receiver. Only the knowledge of the spreading code for the user(s) of interest is exploited here. The proposed technique is shown to outperform existing comparable receiver estimation procedures.

In this paper, we propose a novel algorithm for the MLSE equalizer for the GSM system. Specifically, we use a parametric model for the channel, to obtain a modified Viterbi equalizer which we refer to as the parametric channel-Viterbi equalizer (PC-VE). In contrast to the conventional Viterbi equalizer with a FIR channel description, the PC-VE avoids the linear approximation error and has a lower computational complexity. The proposed algorithm is applicable to both single and multi-antenna receivers. Some simulation results that illustrate the performance of the proposed algorithm are presented.

This paper reviews space-time signal processing in mobile wireless communications. Space-time processing refers to the signal processing performed in the spatial and temporal domain on signals received at or transmitted from an antenna array, in order to improve performance of wireless networks. We focus on antenna arrays deployed at the base stations since such applications are of current practical interest.

Recently, a number of classes of multipath channels which are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra have been presented. In this paper, we consider the blind identification problem of these channels using multiple antennas and show that they will not in general give rise to any common roots among the sub-channels formed from the antennas, and hence, they can be identified from second-order statistics.

The consider the problem of recovering p synchronous communication signals that are transmitted through a multiple-input/multiple-output (MIMO) linear channel and are, therefore, received in the presence of both interuser (IUI) and intersymbol interference (ISI). A multichannel linear equalization approach is taken, and we propose to adjust the equalizer coefficients with a blind adaptive algorithm (without the use of training data). This multiuser constant modulus algorithm (MU-CMA) is derived from the minimization of a cost function that penalizes deviations of the equalized signals from the constant modulus property as well as cross-correlations between them. The proposed scheme appears to be an appealing technique for multiuser blind equalization that combines good convergence properties with low computational complexity.

Recently, Ding (see IEEE Signal Processing Lett., vol.3, p.150-2, May 1996) has pointed out several classes of multipath channels that are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra. In this letter, we consider the blind identification problem using multiple antennas and show that the multipath channels will not give rise to any common roots among the subchannels formed from the antennas and, hence, they can be identified from second-order statistics. In our development, we will point out the role of band-limitedness of the channels in characterizing different classes.

Assuming a multipath propagation scenario, we derive a closed-form subspace-based method for the simultaneous estimation of arrival angles and path delays from measured channel impulse responses, using knowledge of the transmitted pulse shape function and assuming a uniform linear array and uniform sampling. The algorithm uses a two-dimensional (2-D) ESPRIT-like shift-invariance technique to separate and estimate the phase shifts due to delay and direction-of-incidence, with automatic pairing of the two parameter sets. A straightforward extension to the multiuser case allows to connect rays to users as well.

In contrast to conventional array processing, in many applications, such as mobile communications, the concept of a parametric array manifold is ill defined. In mobile communications the loss of a well defined array manifold can be attributed to the complex propagation environment consisting of multiple local scatterers near the mobile and remote dominant scatterers, as well as other co-channel signals. In such applications, estimation methods developed in the conventional setting of array processing are of little use and blind estimation of the transmitted signals is of real importance. We present an unconditional maximum likelihood (UML) approach for blind estimation of multiple co-channel digital BPSK signals received by an antenna array, along with the array response matrix A. Based on the idea of fixed point iteration, an efficient algorithm is derived to obtain the UML estimate of A and the maximum a posteriori (MAP) estimates of the digital signals. Simulation results are presented to demonstrate the improved performance of the proposed UML method over the conventional conditional ML (CML) methods. An upper bound on the bit error rate is also presented.

Singular value analysis of a GMSK-modulated signal such as employed by GSM reveals that it admits a reasonably accurate linear model, enabling the use of linear space-time equalizers to retrieve the data symbols. The analysis also shows that one antenna does not provide sufficient resolution to allow estimation of the channel length, so that the performance of the equalizers is limited. An algorithm is proposed for the blind space-time equalization and separation of multiple co-channel GMSK signals, based on their fixed symbol rate, finite alphabet and constant modulus properties.

An antenna array-based base station receiver structure for wireless direct-sequence code-division multiple-access (DS/CDMA) with M-ary orthogonal modulation is proposed. The base station uses an antenna array beamformer-RAKE structure with noncoherent equal gain combining. The receiver consists of a "front end" beamsteering processor feeding a conventional noncoherent RAKE combiner. The performance of the proposed receiver with closed loop power control in multipath fading channels is evaluated. Expressions for the system uncoded bit-error probability (BEP) as a function of the number of users, number of antennas, and the angle spread are derived for different power control scenarios. The system capacity in terms of number of users that can be supported for a given uncoded BEP is also evaluated. Analysis results show a performance improvement in terms of the system capacity due to the use of antenna arrays and the associated signal processing at the base station. In particular, analysis results show an increase in system capacity that is proportional to the number of antennas. They also show an additional performance improvement due to space diversity gain provided by the array for nonzero angle spreads.

Adaptive transmitting antenna arrays can increase the capacity of mobile radio networks by reusing a channel among several users. To reuse bandwidth, a transmitting antenna array can exploit feedback information from the mobile receivers in order to track changes in the multipath environment. When the mobile is moving rapidly, the required feedback rates can become significant. We present a new method for transmission beamforming, which, by exploiting the subspace structure present in the spatial channel, requires much lower feedback data rates than previous methods. We consider antenna arrays at the base only, and the mobile has a single omnidirectional antenna. Adaptive Sendeantennen-Arrays können die Kapazität von Mobilfunknetzen mittels Mehrfachnutzung eines Kanals durch verschiedene Teilnehmer vergröβern. Dabei kann ein Sendeantennen-Array Information im Rückkanal auswerten, um Änderungen der Mehrwegeausbreitung folgen zu können. Wenn die Mobilstation sich sehr schnell bewegt, können die benötigten Datenraten im Rückkanal erheblich werden. Wir stellen eine neue Methode für die Sendekeulenformung dar, welche unter Ausnutzung der in den räumlich getrennten Kanälen vorliegenden Subspace-Struktur wesentlich niedrigere Datenraten im Rückkanal benötigt als vorherige Methoden. Wir betrachten Antennen-Arrays nur an den Basisstationen, die Mobilstation hat eine einzige omnidirektionale Antenne. Les réseaux adaptatifs d'antennes émettrices peuvent améliorer la capacité des réseaux de radio mobile en réutilisant un canal parmi plusieurs utilisateurs. Afin de réutiliser une largeur de bande, un réseau d'antennes émettrices peut exploiter l'information de feed-back en provenance des récepteurs mobiles afin de dépister les changements dans l'environement à plusieurs chemins. Quand un objet en mouvement se déplace rapidement, les taux de feed-back requis peuvent devenir significatifs. On présente une nouvelle méthode pour le formattage d'antenne émettrice qui, en exploitant la structure de sous-espace présente dans le canal spatial, requière des taux de feed-back de données bien moindres que ceux présentés dans d'autres méthodes. On considère des réseaux d'antennes seulement sur la station de base, et l'objet en mouvement avec une seule antenne omni-directionelle.

An approach to mitigate forward link signal fading in a FDD communication system by using an adaptive transmit antenna array and feedback on the reverse link is presented. In a personal communication system environment, multipath propagations can lead to severe space selective fading. Cordless phones and similar devices which cannot conveniently provide multiple antennas at the receiver can suffer from long term fading and therefore have unacceptable quality. Using multiple adaptive transmit antennas, we can adjust the transmission weights to ensure the user is kept out of deep fades. This is achieved by using feedback of the received signal level on the reverse link and adapting the transmission weights. Simulation shows that significant gain against the fading characteristics can be achieved.

A simple adaptive technique is proposed for separation and demodulation of multiple co-channel frequency modulated (FM) signals received at an antenna array. The proposed method, which for FM signals is embodied in an architecture referred to as a multitarget adaptive phase-lock loop (MADPLL), exploits known signal structure through a complete demodulation and remodulation of the signals. The two properties of the signal that are exploited here are the known bandwidth of the information signal and the constant-modulus (CM) property of FM signals. It is shown that the proposed method can lead to significant improvements in performance over methods that exploit only the CM property.

The finite alphabet property of digital communication signals, along with oversampling techniques, enables the blind identification and equalization of an unknown FIR channel carrying a superposition of such signals, provided they have the same (known) period. Applied to multi-user wireless communications, the same framework allows the blind separation of multiple finite alphabet signals received at all arbitrary antenna arrays through an unknown multipath propagation environment with finite delay spread. An algorithm is proposed and tested on simulated data.

High-resolution algorithms for direction finding of narrowband sources require a good estimate of the noise correlation matrix. We derive a physically motivated linear noise model. It is based on a Fourier expansion of the ambient noise field and is applicable to arbitrary antenna arrays. We also show that for contrived cases, a linear model may not be uniquely identifiable.>

Using oversampling and the finite-alphabet property of digital communication signals, it is possible to blindly identify an FIR channel carrying a superposition of such signals, provided they have the same (known) period, and certain rank conditions on the data and channel matrices are satisfied. In particular, this technique allows separation of finite alphabet signals, removal of intersymbol interference, and synchronization of the signals. An algorithm is proposed and tested on simulated data.>

Currently, a central base station communicates simultaneously with several mobile users by allocating a separate time or frequency channel for each mobile to prevent undesired crosstalk. However, each time or frequency channel may be reused among several mobiles by means of an antenna array at the base station which points a separate beam at each user. The downlink beamformer would normally operate in an "open loop" mode, in which the base steers a mainlobe in the direction of each mobile. Such a system may operate effectively in a free space environment with no multipath. In the presence of scattering, open loop methods will not perform adequately. A new "closed loop" technique is presented in which each mobile user feeds back to the base estimates of the received signal amplitudes. Using feedback, the base station can achieve precision beamforming resulting in lower crosstalk and improved signal separation even in the presence of strong scattering environments.>

Mobile radio channels can be generally characterized as a fading multipath channel with multipath spread delay that ranges from a few microseconds (/spl mu/s) up to as much as 15 /spl mu/s. Such large delays result in intersymbol interference which raises the need for equalization. A semi-blind maximum likelihood sequence estimation (MLSE) with an antenna array is studied as an adaptive equalization method for time division multiple access (TDMA) digital cellular systems. The MLSE is implemented using a Viterbi algorithm (VA). An antenna array is used to utilize both temporal and spatial structure in the received signal to provide the VA with the estimate of the channel impulse response necessary for it to perform MLSE.>

We address the problem of transmitting multiple cochannel signals from an antenna array to several receivers so that each receiver gets its intended signal with minimum crosstalk from the remaining signals. In addition to the usual "information" mode, we propose a "probing" mode during which probing signals received at the mobiles are fed back to the transmitter. These probing signals are used to identify an unknown propagation environment, enabling the transmitter to form the necessary transmission beampatterns.>

Proposes a novel approach for separating and estimating multiple co-channel digital signals using an antenna array. The spatial response of the array is unknown. The authors exploit the temporal structure of the digital signals to simultaneously determine the array response and the bit sequence for each signal. Uniqueness of the estimates is established for signals with BPSK modulation format. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful in digital mobile communications. Simulation results demonstrate its promising performance.>

The authors present a parallel algorithm for logic simulation of VLSI circuits. It is implemented on a network of transputers connected in a ring topology. The approach is based on partitioning a functionality matrix representation of the circuit among the transputers and adopting a data flow technique for the solution. A significant aspect of the algorithm is that it overlaps computation with communication, thereby reducing the communication overhead. It also attempts even distribution of load in order to reduce processor idle time. The algorithm possesses the advantages of ease of implementation and ease of extension to incorporate additional parameters for simulation. Performance results of the algorithm are given.>

Article Free Access Share on Loop partitioning for distributed memory multiprocessors as unimodular transformations Authors: D. Kulkarni Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , K. G. Kumar Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , A. Basu Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , A. Paulraj Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile Authors Info & Claims ICS '91: Proceedings of the 5th international conference on SupercomputingJune 1991 Pages 206–215https://doi.org/10.1145/109025.109079Published:01 June 1991Publication History 7citation207DownloadsMetricsTotal Citations7Total Downloads207Last 12 Months7Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A general solution for extending subspace techniques to maneuvering platforms is proposed. The method involves a matrix transformation that uses an approximate guess of the DOAs (directions of arrival) and knowledge of the platform orientation corresponding to each data set to transform the available data to a consistent datum subspace. Any subspace estimation technique, such as the MUSIC, ESPRIT, or maximum likelihood methods, can then be used to arrive at the DOA estimation solution. If necessary, the solution obtained can be iteratively improved by using the estimated DOAs at each iteration for deriving the transformation needed in the next iteration. Apart from maneuvering arrays, the proposed method is of interest in compensating for unavoidable platform motion arising due to large amounts of pitch, roll, or yaw.>

ESPRIT is a new algorithm for signal parameter estimation with applications to direction-of-arrival estimation in a multiple source environment. It has considerable computational advantages (e.g., faster and applies to sensor arrays with unknown and nearly arbitrary geometry requiring no array calibration and storage) over the well-known conventional MUSIC algorithm. Herein, results of computer simulations carried out to compare their resolution and error (bias and variance) performance are presented. A new multi-dimensional spectral measure for the MUSIC algorithm is also introduced and preliminary investigations of its performance are presented.

The application of the eigenstructure algorithm for estimating the Doppler (frequency shift) of wideband signals in noise is described. The problem is formulated in the context of a FM-CW radar where, the target range appears as a frequency shift which is then estimated. Our approach generalizes the well known results of Pisarenko for determining the Doppler (frequency shifts) of multiple harmonics in noise to the problem of estimating the frequency shifts of multiple wideband signals. Results of computer simulations that verify the performance of our proposed algorithm are also presented.

Results of simulations comparing the performance of ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) and the MUSIC (MUltiple Signal Classification) algorithm are presented. ESPRIT exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. In contrast, the MUSIC algorithm uses intersections between the array manifold and the signal subspace to estimate the directions. ESPRIT is shown to have performance advantages over MUSIC in certain scenarios apart from its previously reported implementational advantages.

We propose a statistical procedure known as the smoothed rank profile (SRP) test that can be applied to an array covariance matrix to determine the source coherency structure and solvability of the directions-of-arrival estimation problem in the presence of coherent sources. The SRP is the rank profile of a telescoping series of matrices extracted from the observed array covariance matrix. Results of computer simulations are presented that verify the efficacy of the proposed test.

Eigenstructure methods for direction of arrival estimation have become well established for radar, sonar and radio array applications for which coherent (i.e. amplitude and phase) measurements are available. In many IR and optical applications incoherent detectors are used that measure the power rather than signal amplitude/phase. In this paper, we derive a subspace algorithm for high resolution direction of arrival estimation for such measurement models. Results of computer simulation that verify the performance of our proposed algorithm are also presented.

The MUSIC algorithm is one of the more important high resolution approaches for direction finding and spectral estimation that have been developed in recent years. Asymptotically (i.e. infinite data or SNR) the MUSIC algorithm has been shown to yield efficient unbiased estimates. However the performance of the algorithm for the non-asymptotic situation of high noise and limited data has not been fully addressed. In this paper we study the performance of the MUSIC algorithm when only finite noise corrupted data is available. We focus on the role of array design in the performance of MUSIC algorithm for direction finding and introduce certain measures to characterize its performance. We show that in the single target situation these measures can be described in terms of the familiar conventional beampatterns. Results of computer simulations carried out to check the usefulness of such measures are also presented.

A new approach to Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) is described in the context of direction-of-arrival estimation, but is also applicable to other problems. The method relies on finding the underlying rotation between the common subspaces associated with an array of pairwise-matched and codirectional sensor doublets. ESPRIT has several remarkable advantages over earlier techniques such as MUSIC, and also provides asymptotically unbiased and efficient estimates.

We consider a source radiated signal arriving at an array as a group of wavefronts, each having a different angle of arrival and with arbitrary amplitude, phase and inter wavefront correlation. Several such sources may be present and the measurement data is assumed to be corrupted by sensor to sensor uncorrelated noise. The task of the beamformer is to make optimal estimates of each source signal of interest by using the information in all the wavefronts generated by the source. The proposed processor begins with no apriori information about the environment and constructs the optimal beamformer by a bootstrapping approach which uses a two tier eigenstructure analysis of the array covariance. We show that this new beamformer has substantial advantages over the usual optimal beamformers and present results of computer simulation carried out to verify its performance.

Direction of arrival estimation by eigenstructure methods requires knowledge of the array covariance matrix and an exact characterization of the array in terms of geometry, sensor gain and phase, etc. It often happens that the actual sensor gain and phase are perturbed from their assumed nominal values. If eigenstructure methods are applied with incorrect sensor parameters, the method essentially breaks down or at best gives poor results. We propose a new approach which uses information in the observed covariance matrix to correct for these effects. This method yields substantially improved performance, a fact illustrated by the results of computer simulations.