Antenna Subset Selection Research Articles

Space-Time Block Codes with Limited Feedback Using Antenna Grouping

We propose an antenna grouping method that improves the error rate performance of space-time codes in a wide range of mobility environments. The idea is to group symbols to antennas based on limited feedback from the mobile station to utilize all antennas. Our approach requires only two bits of feedback information to achieve better link performance and full rate for a certain four transmit antenna system. Numerical results confirm the bit/frame error gains over the Alamouti-based space-time block code and antenna subset selection strategies.

Capacity Limits of Multiple Antenna Multicasting Using Antenna Subset Selection

Both military and commercial wireless cellular networks often require the same data to be conveyed to multiple users simultaneously. This technique is usually referred to as physical layer multicasting. Unfortunately, the capacity of this multicasting setup is dictated by the smallest maximum achievable rate among all the users. In this paper, we consider the use of antenna subset selection in multicast channels where the transmitter is equipped with multiple antennas and sends a common message to multiple users. In this set-up, the antenna subset selection scheme selects some subset of the basestation transmit antennas to maximize the minimum signal-to-noise ratio (SNR) among the associated users. Using an asymptotic analysis, the average capacity of the antenna subset selection scheme is compared with that provided by max-min transmit beamforming, which requires channel state information at the transmitter to maximize the minimum user SNR, and an open-loop scheme where independent data is transmitted on each antenna. Then, we identify the minimum required antenna configuration condition for multicasting in which the antenna subset selection scheme universally performs better than the open-loop scheme and outperforms max-min transmit beamforming when the number of users is large. In addition, for a fixed number of radio frequency chains and users, it is shown that the antenna subset selection scheme can exploit the antenna selection diversity and its average capacity grows double logarithmically with the number of transmit antennas without bound.

Optimal Diversity Performance of Space Time Block Codes in Correlated Distributed MIMO Channels

This paper investigates optimal transmission of space-time block codes (STBCs) in distributed multiple-input multiple-output (D-MIMO) Rayleigh fading channels. The optimal diversity performance is achieved through transmit power allocation implemented at the receiver based on transmit and receive correlations to minimize the average symbol error rate (SER). Evaluation of SER performance of uncoded STBCs over a generalized distributed antenna (DA) topology is first presented, with exact analytical SER expressions derived for MQAM and MPSK symbols. SER upper bounds are also derived, based on which two criteria for complexity reduced antenna subset selection with sub-optimal power allocation are further proposed, whose performance approaches optimal over correlated D-MIMO channels. Moreover, a novel simplified but close SER approximation scheme is devised to significantly facilitate optimal SER calculation. We continue to thoroughly analyze how the optimal diversity is affected by large scale fading, targeted data rate, antenna correlations and transmit power. Finally, we develop a surprisingly close and useful analogy between open loop STBCs in co-located MIMO and optimal STBCs in D-MIMO with minimum feedback (i.e., n bits for n DAs in Criterion 2 with power allocation scheme 2 which equally allocates power to the selected DAs). Extensive simulation results have been presented to demonstrate the effectiveness of our analysis.

Capacity Based Fast Receive Antenna Subset Selection in MIMO System

In this letter, we develop a two-step receive antenna selection method to maximize channel capacity. Different from previous work, we first derive a lower bound on capacity based on Hadamard inequality and arithmetic-geometric mean inequality, which is then used to iteratively drop the worst-performing antennas according to their measure. The recursive nature of this method helps to largely reduce the computational complexity.

Antenna and User Subset Selection in Downlink Multiuser Orthogonal Space-Division Multiplexing

Block diagonalization (BD) and successive optimization (SO) are two suboptimal but more practical (compared to dirty paper coding (DPC)) orthogonal linear precoding techniques for the downlink of multiuser MIMO systems. Since the numbers of users supported by BD or SO for a given number of transmit antennas are limited, BD or SO should be combined with scheduling so that a subset of users is selected at a given time slot while meeting the dimensionality requirements of these techniques. On the other hand, receive antenna selection (RAS) is a promising hardware complexity reduction technique. In this paper, we consider user scheduling in conjunction with receive antenna selection. Since exhaustive search is computationally prohibitive, we propose simplified and suboptimal user scheduling algorithms for both BD and SO. For BD, we propose capacity and Frobenius-norm based suboptimal algorithms with the objective of sum rate maximization. Starting from an empty set, each step of proposed algorithms adds the best user from the set of users not selected yet until the desired number of users have been selected. Proposed receive antenna selection works in conjunction with user scheduling to further enhance the sum rate of BD. For SO, a Frobenius-norm based low complexity algorithm is proposed, which maximizes the ratio of the squared Frobenius norm of the equivalent channel (projected to the joint null space of the previously selected users) to the sum of the squared Frobenius norms of the previously selected users' preprocessed channels. Simulation results demonstrate that the proposed algorithms achieve sum rates close to exhaustive search algorithms with much reduced complexity. We also show that in addition to reduced hardware complexity at the receiver, antenna selection enhances multiuser diversity gain that is achieved with user scheduling.

Antenna Subset Selection for Cyclic Prefix Assisted MIMO Wireless Communications over Frequency Selective Channels

Antenna (subset) selection techniques are feasible to reduce the hardware complexity of multiple-input multiple-output (MIMO) systems, while keeping the benefits of higher-order MIMO systems. Many studies of antenna selection schemes are based on frequency-flat channel models, which are inconsistent to broadband MIMO systems employing spatial-multiplexing. In broadband MIMO systems aiming to provide high-data-rate links, the employed signal bandwidth is typically larger than the coherence bandwidth of the channel so that the channel will be of frequency selective nature. Within this contribution we provide an overview on joint transmitter-and receiver-side antenna subset selection methods for frequency selective channels and deploy them in MIMO orthogonal frequency division multiplexing (OFDM) systems and MIMO single-carrier (SC) systems employing frequency domain equalization (FDE).

A Diversity Guarantee and SNR Performance for Unitary Limited Feedback MIMO Systems

A multiple-input multiple-output (MIMO) wireless channel formed by antenna arrays at the transmitter and at the receiver offers high capacity and significant diversity. Linear precoding may be used, along with spatial multiplexing (SM) or space-time block coding (STBC), to realize these gains with low-complexity receivers. In the absence of perfect channel knowledge at the transmitter, the precoding matrices may be quantized at the receiver and informed to the transmitter using a feedback channel, constituting a limited feedback system. This can possibly lead to a performance degradation, both in terms of diversity and array gain, due to the mismatch between the quantized precoder and the downlink channel. In this paper, it is proven that if the feedback per channel realization is greater than a threshold, then there is no loss of diversity due to quantization. The threshold is completely determined by the number of transmit antennas and the number of transmitted symbol streams. This result applies to both SM and STBC with unitary precoding and confirms some conjectures made about antenna subset selection with linear receivers. A closed form characterization of the loss in SNR (transmit array gain) due to precoder quantization is presented that applies to a precoded orthogonal STBC system and generalizes earlier results for single-stream beamforming.

Loading Algorithm for Multicarrier Spatial Diversity Systems with Antenna Selection

In this paper, a novel loading algorithm consisting of four variants is proposed for a multicarrier transceiver employing multiple antennas configured for spatial diversity. The primary objective of the proposed algorithm is to increase the overall throughput while ensuring the mean bit error rate (BER) is below a specified limit. To achieve this, spatial diversity is employed to improve the subcarrier signal-to-noise ratio (SNR) values. Simultaneously, (uniform or non-uniform) bit allocation, which is a function of subcarrier SNR, is performed to increase throughput. To reduce power consumption, spatial processing complexity, and hardware costs, antenna subset selection is also performed by the proposed algorithm to choose a set of active transmit/receive antennas. The results show that combining bit allocation with spatial diversity (employing antenna subset selection) can yield substantial throughput increases.

Optimal antenna subset selection and blind detection approach applied to orthogonal space-time block coding

An approach combining optimal antenna subset selection with blind detection scheme for Orthogonal Space-Time Block Coding (OSTBC) is proposed in this paper. The optimal antenna subset selection is taken into account at transmitter and/or receiver sides, which chooses the optimal antennas to increase the diversity order of OSTBC and improve further its performance. In order to enhance the robustness of the detection used in the conventional OSTBC scheme, a blind detection scheme based on Independent Component Analysis (ICA) is exploited which can directly extract transmitted signals without channel estimation. Performance analysis shows that the proposed approach can achieve the full diversity and the flexibility of system design by using the antenna selection and the ICA based blind detection schemes.

Suboptimal Transmission of Orthogonal Space–Time Block Codes Over Correlated Distributed Antennas

This letter investigates optimal transmission of orthogonal space-time block codes (OSTBCs) over distributed antennas (DAs) in non-ergodic flat Rayleigh fading channels with transmit antenna correlations. A generalized DA topology is considered, where the DAs are grouped into some geographically dispersed ports within each of which the DAs are co-located. Assuming equal power allocation within each port, the outage probability is derived. We find that minimizing the outage probability only requires the feedback of the eigenvalues of the transmit correlation matrix at the transmitter. Since it is computationally intensive to minimize the outage probability, an antenna subset selection with suboptimal power allocation scheme is proposed, whose effectiveness has been demonstrated by numerical results

Receive antenna selection for MIMO-SM systems with linear MMSE receivers in the presence of unknown interference

In this paper, a novel receive antenna subset selection technique is proposed for multiple input multiple output spatial multiplexing (MIMO-SM) systems with linear minimum mean square error (MMSE) receivers in the presence of unknown co-channel interference. This antenna selection technique is directly implemented based on training sample sequence by utilizing backward greedy algorithm (BGA) under the least squares (LS) criterion. In the case of practical implementation. Diagonal loading (DL) technique is incorporated into the selection process to insure robustness of antenna selection given limited training sample support. Simulation results show that the proposed antenna selection technique is able to retain the diversity order of a full complexity system in the presence of unknown multiple access interference (MAI)

Efficient Capacity-Based Joint Transmit and Receive Antenna Selection Schemes in MIMO Systems

In this letter, we propose two different joint transmit and receive antenna subset selection schemes for multiple-input multiple-output (MIMO) systems on the basis of capacity maximization criterion. We assume that perfect channel state information (CSI) is known at the receiver but unknown to the transmitter. As the selection signaling is perfectly fed back to the transmitter, we propose a flexible two-step selection algorithm (TSSA) in practical MIMO channel scenarios. Computer simulations show that TSSA can maximize the capacity at low computation cost in most scenarios. It performs well in terms of capacity, computational complexity and flexibility. Furthermore, we propose a simplified algorithm based on the correlation matrix when the channel correlation information (CCI) is known to the transmitter. Simulation results show that the proposed correlation matrix based selection algorithm is only slightly inferior to an optimal selection algorithm.

Antenna subset selection in measured indoor channels

Antenna subset selection can greatly reduce the implementation complexity of multiple input multiple output (MIMO) systems while retaining most of their benefits. This paper investigates the diversity gain and capacity of such systems in wireless personal area networks. Considered scenarios include both the communication between access point to a laptop, and between two handheld devices. We analyse the performance of different antenna selection algorithms and signal combining methods in measured dual-polarised narrowband and wideband propagation channels. We find that line-of-sight and non-line-of-sight situations have fairly similar behaviour. Different polarisations result in similar signal-to-noise ratio gains when the multiple antennas are used for diversity, but result in noticeably different capacities in spatial-multiplexing systems. We also find that radiofrequency (RF) preprocessing of the signals is less effective for handheld handsets with non-uniform antenna arrangements than for uniform linear arrays. For communications between handheld devices, simple selection (of one out of four antennas) shows extremely high performance gains compared to no-selection. Finally, we compare bulk selection (same antenna subset is used for all frequency sub-channels) to per-tone selection (different antenna subsets can be used for each frequency sub-channel) for wideband channels. Bulk selection together with RF preprocessing performs almost as well as per-tone selection for some scenarios.

Cross-entropy optimisation of multiple-input multiple-output capacity by transmit antenna selection

Radio channel capacity can be increased dramatically using a multiple-input multiple-output (MIMO) scheme, but at the expense of hardware complexity. An efficient approach for complexity reduction is antenna subset selection at the transmitter and/or receiver. A novel transmit antenna selection algorithm is presented using the cross-entropy optimisation method to maximise channel capacity. In contrast with the existing work, the proposed algorithm guarantees a result to within 99% of the true optimum (i.e. the maximal capacity with selected transmit antennas) with substantially low complexity. The simulation results indicate that the proposed algorithm is independent of the relationship between the selected transmit array size and receive array size. The proposed scheme has the potential to make practical MIMO systems with high performance simpler to implement.

Receive antenna subset selection based on orthogonal components

A new receive antenna subset selection algorithm with low complexity for wireless Multiple-Input Multiple-Output (MIMO) systems is proposed, which is based on the orthogonal components of the channel matrix. Larger capacity is achieved compared with the existing antenna selection methods. Simulation results of quasi-static flat fading channel demonstrate the significant performance of the proposed selection algorithm.

Extended Techniques for Transmit Antenna Selection With STBCs

In this paper, we consider transmit antenna selection (TAS) with space-time block codes (STBCs). We consider a general framework for TAS which, besides antenna subset selection, includes the possibility of having more than one STBC to choose from as well as non-uniform power allocation. Also, to limit the number of transmit RF chains, we require that the maximum (row) rank of the STBC matrices have an upper limit. Simple analysis indicate that transmitting uncoded data via the transmit antenna with the largest Frobenius norm, which can be viewed as a particular case of TAS with orthogonal STBC (OSTBC), not only provides full diversity as if all the transmit antennas were used but also has larger signal-to-noise ratio as compared to TAS with any standard OSTBC (like the Alamouti code). This suggests that TAS with non-orthogonal STBCs should be considered, in particular by means of exploiting instantaneous coherence within subsets of antennas. A few TAS schemes are proposed and computer simulations are used to demonstrate their superior error performance.

Adaptive Antenna Subarray Formation for MIMO Systems

MIMO systems with reduced hardware complexity have attracted researchers' attention due to their high efficiency and low cost. Sub-optimum algorithms for antenna subset selection have been intensively studied in the literature. In this paper we present a new technique to maximize the capacity of multiple antenna wireless systems with reduced available RF chains. The technique is based on the adaptive formation of subarrays, i.e. the grouping of antenna elements and the application of appropriate element weights. The elements of each subarray and their weights are dynamically selected by an evolutionary optimization technique using the link capacity as a cost function

Outage Probability Based Optimal Transmission of Space Time Block Codes over Correlated Distributed Antennas

Aiming to optimally transmit space-time block codes (STBCs) over distributed antennas (DAs), this paper examines downlink transmit antenna subset selection with power allocation for STBCs in non-ergodic Rayleigh fading channels with receive antenna correlations. Closed-form outage probability is first derived, which is a function of data rate, rate of STBCs, transmit power, large-scale fading (shadowing and path loss), power allocation weights to each DA and receive antenna correlation. However, achieving the optimal power allocation solution is computationally demanding and the use of sub-optimal techniques is necessitated. Assuming feedback of eigenvalues of transmit and receive antenna correlation matrix at the transmitter and accurate channel state information (CSI) at the receiver, an antenna subset selection with sub-optimal power allocation scheme is proposed, whose performance approaches optimal. The effectiveness of this sub-optimal method has been demonstrated by numerical results.

Receive antenna selection in MIMO systems using convex optimization

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

Interference Mitigation in MIMO Systems by Subset Antenna Transmission

This paper investigates subset antenna transmission (SAT) for multiple-input multiple-output (MIMO) systems in the presence of strong dominant co-channel interferer. The capacity gain from SAT is investigated in the context of optimal antenna subset selection and power allocation. The SAT does not require channel state information of the co-channel interference, and achieves capacity gains by distributing the transmit power equally over a selected subset of the transmit antennas. The capacity gain of the SAT method is analyzed in terms of transmit power and eigenvalues of channel matrix, and its performance in V-BLAST MIMO systems with various signal constellations is evaluated by computer simulation.