Energy and spectral efficiency improvement using improved shark smell-coyote optimization for massive MIMO system

Massive multiple-input multiple-output (MIMO) can considerably enhance the “spectral efficiency and energy efficiency” since it is a major technique for future wireless networks. Thus, the performance needs a huge count of base station antennas to serve a smaller number of terminals in conventional MIMO methodology. Large-scale radio frequency (RF) chains represent the large-scale antennas. There is a need of implementing an effective massive MIMO system for maximizing the efficient performance of the system with high “spectral efficiency and energy efficiency” owing to the high cost of RF chains, and the higher power consumption. In this paper, a massive MIMO communication system is implemented to satisfy the requirements regarding “energy efficiency and spectral efficiency.” Here, the number of base station antennas, the transmit power, and beam forming vectors are optimized to maximize “energy efficiency and spectral efficiency” when the channel capacity is known to be higher than some threshold values. The novelty of this work is a new hybrid optimization adaptive shark smell-coyote optimization (ASS-CO) algorithm is developed for improving energy efficiency. The optimization is done with the help of the hybrid optimization ASS-CO Algorithm. The proposed ASS-CO algorithm-based massive MIMO communication system is evaluated by experimental analysis. From the result analysis, the maximum resource efficiency is observed by SS-WOA, which is 6.6%, 50%, 6.6%, 6.6%, and 6.6% maximized than rider optimization algorithm (ROA), spotted hyena optimization (SHO), lion algorithm (LA), Shark Smell Optimization (SSO), and Coyote Optimization Algorithm (COA) by taking the count of base stations as 4. The superior performance enhancement regarding “spectral efficiency and energy efficiency” is accomplished over the traditional systems.     

二进制猫群算法在大规模MIMO天线选择中的应用

在多输入多输出(MIMO)系统中,天线选择技术平衡了系统的性能和硬件开销,但大规模MI-MO系统收发端天线选择复杂度问题一直没有得到很好的解决.基于信道容量最大化的准则,采用两个二进制编码字符串分别表示发射端和接收端天线被选择的状态,提出将二进制猫群算法(BCSO)应用于多天线选择中,以MIMO系统信道容量公式作为猫群的适应度函数,将收发端天线选择问题转化为猫群的位置寻优过程.建立了基于BCSO的天线选择模型,给出了算法的实现步骤.仿真结果表明所提算法较之于基于矩阵简化的方法、粒子优化算法具有更好的收敛性和较低的计算复杂度,选择后的系统信道容量接近于最优算法,非常适用于联合收发端天线选择的大规模MIMO系统中.     

基于延迟自相关双门限的短波天线选择方法

短波固定台站配有多副发信天线,在实际应用时,一般是根据预先方案选择一副天线发射信号,没有充分利用天线的方向性,因而通信效果并不是最佳.针对这一问题,设计了一种能够在收发双方进行天线发送信号质量评估的探测机制,通过基于延迟自相关运算的双门限检测技术,在收接端判决各发信天线探测信号质量,然后根据评估分值,从短波固定台站众多的天线中自动选择通信效果最佳的发信天线发射信号,在不改变现有配置的情况下最大限度地提升通信质量.仿真结果表明,该方法可行有效,能够以较小的代价提高天线选择效率,充分利用天线的方向性,达到提升发射效率和通信效果的目的.     

可见光多天线空分键控技术研究

空分键控是一种新型的空间复用技术,每个时刻只有一个发送天线工作,携带信息的是天线的位置而非发送符号本身,因此该种方法频带利用率较低。为了提高频带利用率,基于广义空间调制的概念,提出了光多天线空分键控调制方法,这种调制方式中每个时刻有多个天线同时工作。首先建立了可见光通信中的多天线空分键控系统模型,并对其误码率性能进行了分析,然后由此为依据提出了一种基于最小距离最大化准则的天线选择算法以获得误码率性能的增益,最后通过蒙特卡罗仿真验证了该天线选择方法的有效性。      

Spatial Modulation

Spatial modulation (SM) is a recently developed transmission technique that uses multiple antennas. The basic idea is to map a block of information bits to two information carrying units: 1) a symbol that was chosen from a constellation diagram and 2) a unique transmit antenna number that was chosen from a set of transmit antennas. The use of the transmit antenna number as an information-bearing unit increases the overall spectral efficiency by the base-two logarithm of the number of transmit antennas. At the receiver, a maximum receive ratio combining algorithm is used to retrieve the transmitted block of information bits. Here, we apply SM to orthogonal frequency division multiplexing (OFDM) transmission. We develop an analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed (i.i.d.) Rayleigh channels. The analytical and simulation results closely match. The performance and the receiver complexity of the SM-OFDM technique are compared to those of the vertical Bell Labs layered space-time (V-BLAST-OFDM) and Alamouti-OFDM algorithms. V-BLAST uses minimum mean square error (MMSE) detection with ordered successive interference cancellation. The combined effect of spatial correlation, mutual antenna coupling, and Rician fading on both coded and uncoded systems are presented. It is shown that, for the same spectral efficiency, SM results in a reduction of around 90% in receiver complexity as compared to V-BLAST and nearly the same receiver complexity as Alamouti. In addition, we show that SM achieves better performance in all studied channel conditions, as compared with other techniques. It is also shown to efficiently work for any configuration of transmit and receive antennas, even for the case of fewer receive antennas than transmit antennas.     

Adaptively Grouped Multilevel Space-Time Trellis Codes

Grouped multilevel space-time trellis codes (GMLSTTCs) utilize multilevel coding (MLC), antenna grouping and space time trellis codes (STTCs) for simultaneously providing coding gain, diversity improvement and increased spectral efficiency. The performance of GMLSTTCs is limited due to predefining of the antenna groups. It has been shown that when perfect or partial channel state information is available at the transmitter, the performance and capacity of space-time coded system can be further improved. In this paper, we present a new code designed by combining MLC, STTCs, antenna grouping and channel state information at transmitter, henceforth referred to as adaptively grouped multilevel space time trellis codes (AGMLSTTCs). AGMLSTTCs use a single full-diversity STTC at initial some levels and multiple STTCs at some later levels. The single full diversity STTC at each initial level spans all transmit antennas and the STTC at each later level spans a group of transmit antennas. The channel state information at the transmitter is used to adaptively group the transmit antennas for the later levels. Instantaneous channel power gain is calculated between each transmit antenna and all the receive antennas. A subset of transmit antennas having maximum channel power gain is selected to form a group. The simulation results show that AGMLSTTCs enable to transmit more than one data symbol per time slot with improved error performance over GMLSTTCs with predefined transmit antenna grouping.     

分集接收的STBC-MC-CDMA系统中基于PSO算法的多用户检测

该文提出了一种使用多天线分集接收的空时分组码多载波码分多址(STBC-MC-CDMA)系统中基于粒子群优化(PSO)算法的多用户检测(MUD)方案。当采用多天线分集接收时,各个天线接收的信号经历了相互独立的衰落,导致不同天线分支对应的匹配度函数相互独立。为解决多天线分集接收的多目标优化问题,提出了虚拟Pareto前端的概念,并使粒子按照Pareto优化准则进行速度和位置更新。仿真结果表明,所提方案获得了增强的开发和探索能力,其性能优于常规PSO算法和多目标遗传算法。     

一种用于MIMO系统的快速天线选择算法

在多径衰落环境中, MIMO系统的信道容量随天线数的增加呈线性增加,发射/接收天线选择方法能以很小的性能损失换取射频成本的大幅度降低,使MIMO系统不完全受射频成本的限制。为快速选择出使系统容量最优的发射/接收天线子集,该文提出一种快速天线选择算法的改进算法。该算法通过实时更新优化参数,大大降低计算复杂度。仿真结果表明,该算法在不影响系统容量的情况下大大减少了计算时间。     

Smart versus dumb antennas-capacities and FEC performance

We compare two approaches to use multiple transmit antennas in an FEC coded wireless system: smart antennas use an antenna array to direct a beam in the direction of the dominant transmission path in order to obtain an antenna gain. Another approach is to use multiple transmit antennas for diversity using space-time block codes. Since no knowledge of the channel is required at the transmitter we denote this approach as dumb antennas. Using equivalent single-input channel models we compare smart and dumb antennas in terms of the BER performance and channel capacity and discuss under which conditions it is preferable to use multiple transmit antennas for transmit diversity or for beamforming     

能量效率优化的广义空域调制系统

为了提高能源使用效率,能量效率（EE）是绿色无线通信研究的主要内容。为了有效提高多天线传输系统的能源使用效率,提出了一种基于能量效率优化的广义空域调制（GSM）系统（EE-GSM）。该系统基于最大化能量效率准则,考虑发射天线数较多的情况,首先利用天线选择算法（AS）确定最佳发射天线子集,然后计算适合广义空域调制系统的有效射频通道(RFC)数,从而实现全局能量效率优化设计。仿真结果和分析表明,与传统的AS-MIMO、GSM及SM系统相比,新系统能有效地提高能量效率,并且改善了系统的误码率和容量性能,同时系统最终所需的有效射频通道数一般为2,3或4个,符合绿色通信系统设计原则。      

Antenna selection for spatial multiplexing systems with linearreceivers

Future cellular systems will employ spatial multiplexing with multiple antennas at both the 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, maintenance or handoff. We present a criterion for selecting the optimal antenna subset when linear, coherent receivers are used over a slowly varying channel. 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 algorithm also provides diversity advantage thus making linear receivers useful over fading channels     

Effect of antenna separation on the capacity of BLAST in correlatedchannels

As the base station is usually placed above local clutter, the angular spectrum incident on the base is narrow, inducing correlation among base antenna signals, which reduces the capacity of a multiple transmit and receive antenna systems. In this work the general expression for link capacity is derived, when there is correlation among receive antennas and among transmit antennas. It is found that an antenna separation of 4 wavelengths between nearest neighbors in a linear base array of dually polarized antennas allows one to achieve 80% of the capacity attainable in the uncorrelated antenna case     

Capacity of multiple-antenna systems with both receiver and transmitter channel state information

The capacity of multiple-antenna systems operating in Rayleigh flat fading is considered under the assumptions that channel state information (CSI) is available at both transmitter and receiver, and that the transmitter is subjected to an average power constraint. First, the capacity of such systems is derived for the special case of multiple transmit antennas and a single receive antenna. The optimal power-allocation scheme for such a system is shown to be a water-filling algorithm, and the corresponding capacity is seen to be the same as that of a system having multiple receive antennas (with a single transmitter antenna) whose outputs are combined via maximal ratio combining. A suboptimal adaptive transmission technique that transmits only over the antenna having the best channel is also proposed for this special case. It is shown that the capacity of such a system under the proposed suboptimal adaptive transmission scheme is the same as the capacity of a system having multiple receiver antennas (with a single transmitter antenna) combined via selection combining. Next, the capacity of a general system of multiple transmitter and receiver antennas is derived together with an equation that determines the cutoff value for such a system. The optimal power allocation scheme for such a multiple-antenna system is given by a matrix water-filling algorithm. In order to eliminate the need for cumbersome numerical techniques in solving the cutoff equation, approximate expressions for the cutoff transmission value are also provided. It is shown that, compared to the case in which there is only receiver CSI, large capacity gains are available with optimal power and rate adaptation schemes. The increased capacity is shown to come at the price of channel outage, and bounds are derived for this outage probability.     

Threshold-Based Substream Selection for Closed-Loop Spatial Multiplexing

We propose a low-complexity closed-loop spatial multiplexing method with limited feedback over multi-input-multi-output (MIMO) fading channels. The transmit adaptation is simply performed by selecting transmit antennas (or substreams) by comparing their signal-to-noise ratios to a given threshold with a fixed nonadaptive constellation and fixed transmit power per substream. We analyze the performance of the proposed system by deriving closed-form expressions for spectral efficiency, average transmit power, and bit error rate (BER). Depending on practical system design constraints, the threshold is chosen to maximize the spectral efficiency (or minimize the average BER) subject to average transmit power and average BER (or spectral efficiency) constraints, respectively. We present numerical and Monte Carlo simulation results that validate our analysis. Compared to open-loop spatial multiplexing and other approaches that select the best antenna subset in spatial multiplexing, the numerical results illustrate that the proposed technique obtains significant power gains for the same BER and spectral efficiency. We also provide numerical results that show improvement over rate-adaptive orthogonal space-time block coding, which requires highly complex constellation adaptation. We analyze the impact of feedback delay using analytical and Monte Carlo approaches. The proposed approach is arguably the simplest possible adaptive spatial multiplexing system from an implementation point of view. However, our approach and analysis can be extended to other systems using multiple constellations and power levels.     

Spectral efficiency of distributed antenna system with random antenna layout

The downlink capacity potential of a distributed antenna system (DAS) with random antenna layout is investigated. A low complexity sub-optimal power allocation scheme among transmit antennas is proposed. Simulation results show that with the same antenna density DAS outperforms a co-located antenna system (CAS) in terms of average and outage spectral efficiency.     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

Reduced-Complexity Receiver Structures for Space–Time Bit-Interleaved Coded Modulation Systems

Transmission efficiency in radio channels can be considerably improved by using multiple transmit and receive antennas and employing a family of schemes called space-time (ST) coding. Both extended range and/or improved bandwidth efficiency can be achieved, compared with a radio link with a single transmit and receive antenna. Bit-interleaved coded modulation schemes give diversity gains on fading channels with higher order modulation constellations combined with conventional binary convolutional codes also for the case of a single transmit and receive antenna radio link. In this paper, we study a family of flexible bandwidth-efficient ST coding schemes which combine these two ideas in a narrowband flat-fading channel and single-carrier modems. We address receiver complexity for the case of a large number of transmit antennas and higher order modulation constellations. Especially, we focus on practical configurations, where the number of transmit antennas is greater than that of receive antennas. Simplified receivers using tentative decisions are proposed and evaluated by means of simulations. Tradeoffs between complexity reduction and performance loss are presented. We emphasize systems that are of particular interest in applications where the number of transmit antennas exceeds the number of receive antennas. A system with four transmit antennas with an eight-fold complexity reduction and a performance loss of about 1 dB is demonstrated     

一种基于线性离散码的发射天线选择方案

为了充分利用多天线系统的性能增益,该文提出了一种基于线性离散码的发射天线选择(LDC-TAS)方案。在准静态信道环境下,该文比较了所提方案的3种天线选择准则:最大信道增益准则,最大容量准则和最大化最小后验SNR准则。仿真数据显示,在不同的调制方式如QPSK,8PSK和16QAM环境下,最大化最小后验SNR准则比其他两种准则表现出更好的性能。在相同的频谱效率下,与BLAST-TAS相比,所提方案表现出明显的分集增益;在低信噪比环境下,与STBC-TAS相比,仍有一定的性能增益。     

Capacity achieving high rate space-time block codes

It is well known, that the Alamouti scheme is the only space-time code from orthogonal design achieving the capacity of multiple-input multiple-output (MIMO) wireless communication system with n/sub T/=2 transmit antennas and n/sub R/=1 receive antenna. In this work, we propose the n-times stacked Alamouti scheme for n/sub T/=2n transmit antennas and show that this scheme achieves the capacity in the case of n/sub R/=1 receive antenna. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas we achieve a high portion of the capacity with this scheme.     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.